<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">H. J. Kim</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The effect of statistical disclosure limitation on parameter estimation for a finite population</style></title><secondary-title><style face="normal" font="default" size="100%">J. Survey Statistics and Methodology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">Submitted</style></year></dates><volume><style face="normal" font="default" size="100%">to appear</style></volume><pages><style face="normal" font="default" size="100%">to appear</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kulikowich, J.M.</style></author><author><style face="normal" font="default" size="100%">Leu, D.</style></author><author><style face="normal" font="default" size="100%">Nell Sedransk</style></author><author><style face="normal" font="default" size="100%">Coiro, J.</style></author><author><style face="normal" font="default" size="100%">Forzani, E.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Performance Characteristics of Three Formats for Assessing Internet Research Skills in Science</style></title></titles><dates><year><style  face="normal" font="default" size="100%">Submitted</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Leu,D.</style></author><author><style face="normal" font="default" size="100%">Coiro, J.</style></author><author><style face="normal" font="default" size="100%">Kulikowich, J.M.</style></author><author><style face="normal" font="default" size="100%">W. Cui</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using the Psychometric Characteristics of Multiple-Choice, Open Internet, and Closed (Simulated) Internet Formats to Refine the Development of Online Research and Comprehension Assessments in Science: Year Three of the ORCA Project</style></title></titles><dates><year><style  face="normal" font="default" size="100%">Submitted</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">L. H. Cox</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The World’s Simplest Survey Microsimulator (WSSM)</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Official Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">Submitted</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Phillip Kott</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A design-sensitive approach to fitting regression models with complex survey data</style></title><secondary-title><style face="normal" font="default" size="100%">2015 FCSM Research Conference</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">designbased.</style></keyword><keyword><style  face="normal" font="default" size="100%">extended model</style></keyword><keyword><style  face="normal" font="default" size="100%">generalized cumulative logistic model</style></keyword><keyword><style  face="normal" font="default" size="100%">proportional-odds model</style></keyword><keyword><style  face="normal" font="default" size="100%">Pseudo-maximum likelihood</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://projecteuclid.org/euclid.ssu/1516179619</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Statistics Surveys</style></publisher><isbn><style face="normal" font="default" size="100%">1935-7516</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Fitting complex survey data to regression equations is explored under a design-sensitive model-based framework. A robust version of the standard model assumes that the expected value of the difference between the dependent variable and its model-based prediction is zero no matter what the values of the explanatory variables. The extended model assumes only that the difference is uncorrelated with the covariates. Little is assumed about the error structure of this difference under either model other than independence across primary sampling units. The standard model often fails in practice, but the extended model very rarely does. Under this framework some of the methods developed in the conventional design-based, pseudo-maximum-likelihood framework, such as fitting weighted estimating equations and sandwich mean-squared-error estimation, are retained but their interpretations change. Few of the ideas here are new to the refereed literature. The goal instead is to collect those ideas and put them into a unified conceptual framework.&lt;/p&gt;
</style></abstract><call-num><style face="normal" font="default" size="100%">Vol. 12 (2018) 1–17</style></call-num></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Troia, G. A.</style></author><author><style face="normal" font="default" size="100%">Olinghouse, N. G.</style></author><author><style face="normal" font="default" size="100%">Wilson, J.</style></author><author><style face="normal" font="default" size="100%">Stewart, K. O.</style></author><author><style face="normal" font="default" size="100%">Mo, Y.</style></author><author><style face="normal" font="default" size="100%">Hawkins, L.</style></author><author><style face="normal" font="default" size="100%">Kopke, R.A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Common Core Writing Standards: A descriptive study of content and alignment with a sample of former state standards</style></title><secondary-title><style face="normal" font="default" size="100%">Reading Horizons</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bellow M.E.</style></author><author><style face="normal" font="default" size="100%">Daniel K.</style></author><author><style face="normal" font="default" size="100%">Gorsak M.</style></author><author><style face="normal" font="default" size="100%">Erciulescu A.L.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evaluating Record Linkage Software for Agricultural Surveys</style></title><secondary-title><style face="normal" font="default" size="100%">JSM Proceedings. Survey Research Methods Section. Alexandria, VA: American Statistical Association.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ww2.amstat.org/MembersOnly/proceedings/2016/data/assets/pdf/389754.pdf.</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">3225-3235</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Susan Abbatiello</style></author><author><style face="normal" font="default" size="100%">Birgit Schilling</style></author><author><style face="normal" font="default" size="100%">D.R. Mani</style></author><author><style face="normal" font="default" size="100%">L.I. Shilling</style></author><author><style face="normal" font="default" size="100%">S.C. Hall</style></author><author><style face="normal" font="default" size="100%">B. McLean</style></author><author><style face="normal" font="default" size="100%">M. Albetolle</style></author><author><style face="normal" font="default" size="100%">S. Allen</style></author><author><style face="normal" font="default" size="100%">M. Burgess</style></author><author><style face="normal" font="default" size="100%">M.P. Cusack</style></author><author><style face="normal" font="default" size="100%">M Gosh</style></author><author><style face="normal" font="default" size="100%">V Hedrick</style></author><author><style face="normal" font="default" size="100%">J.M. Held</style></author><author><style face="normal" font="default" size="100%">H.D. Inerowicz</style></author><author><style face="normal" font="default" size="100%">A. Jackson</style></author><author><style face="normal" font="default" size="100%">H. Keshishian</style></author><author><style face="normal" font="default" size="100%">C.R. Kinsinger</style></author><author><style face="normal" font="default" size="100%">Lyssand, JS</style></author><author><style face="normal" font="default" size="100%">Makowski L</style></author><author><style face="normal" font="default" size="100%">Mesri M</style></author><author><style face="normal" font="default" size="100%">Rodriguez H</style></author><author><style face="normal" font="default" size="100%">Rudnick P</style></author><author><style face="normal" font="default" size="100%">Sadowski P</style></author><author><style face="normal" font="default" size="100%">Nell Sedransk</style></author><author><style face="normal" font="default" size="100%">Shaddox K</style></author><author><style face="normal" font="default" size="100%">Skates SJ</style></author><author><style face="normal" font="default" size="100%">Kuhn E</style></author><author><style face="normal" font="default" size="100%">Smith D</style></author><author><style face="normal" font="default" size="100%">Whiteaker, JR</style></author><author><style face="normal" font="default" size="100%">Whitwell C</style></author><author><style face="normal" font="default" size="100%">Zhang S</style></author><author><style face="normal" font="default" size="100%">Borchers CH</style></author><author><style face="normal" font="default" size="100%">Fisher SJ</style></author><author><style face="normal" font="default" size="100%">Gibson BW</style></author><author><style face="normal" font="default" size="100%">Liebler DC</style></author><author><style face="normal" font="default" size="100%">M.J. McCoss</style></author><author><style face="normal" font="default" size="100%">Neubert TA</style></author><author><style face="normal" font="default" size="100%">Paulovich AG</style></author><author><style face="normal" font="default" size="100%">Regnier FE</style></author><author><style face="normal" font="default" size="100%">Tempst, P</style></author><author><style face="normal" font="default" size="100%">Carr, SA</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma.</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular Cell Proteomics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2015</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">2357-74</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was &amp;lt;20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">9</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">H. J. Kim</style></author><author><style face="normal" font="default" size="100%">L. H. Cox</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">Q. Wang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Simultaneous Edit-Imputation for Continuous Microdata</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of the American Statistical Association</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><volume><style face="normal" font="default" size="100%">110</style></volume><pages><style face="normal" font="default" size="100%">987-999</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">H. J. Kim</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Statistical disclosure limitation in the presence of edit rules</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Official Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">121-138</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analytical frameworks for data release: A statistical view</style></title><secondary-title><style face="normal" font="default" size="100%">Confidentiality and Data Access in the Use of Big Data: Theory and Practical Approaches. </style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><publisher><style face="normal" font="default" size="100%">Cambridge University Press</style></publisher><pub-location><style face="normal" font="default" size="100%">New York City, NY</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">J. Zou</style></author><author><style face="normal" font="default" size="100%">G. S. Datta</style></author><author><style face="normal" font="default" size="100%">S. Grannis</style></author><author><style face="normal" font="default" size="100%">J. Lynch</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Bayesian spatio-temporal approach for real-time detection of disease outbreaks: A case study</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Medical Informatics and Decision Making</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2014</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">108</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">R. Ferrell</style></author><author><style face="normal" font="default" size="100%">T. H. McCormick</style></author><author><style face="normal" font="default" size="100%">P. B. Ryan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Big data, big results: Knowledge discovery in output from large-scale analytics</style></title><secondary-title><style face="normal" font="default" size="100%">Statistical Analysis and Data Mining</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2014</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">404-412</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">J. Lane</style></author><author><style face="normal" font="default" size="100%">V. Stodden</style></author><author><style face="normal" font="default" size="100%">H. Nissenbaum</style></author><author><style face="normal" font="default" size="100%">S. Bender</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Confidentiality and Data Access in the Use of Big Data: Theory and Practical Approaches</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><publisher><style face="normal" font="default" size="100%">Cambridge University Press</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">Analytical frameworks for data release: A statistical view</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">H. J. Kim</style></author><author><style face="normal" font="default" size="100%">S. N. MacEachern</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The generalized multiset sampler</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Computational and Graphical Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1080/10618600.2014.962701</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">S. K. Kinney</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">J. Miranda</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Improving the Synthetic Longitudinal Business Database</style></title><secondary-title><style face="normal" font="default" size="100%">Statistical Journal of the IAOS</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><volume><style face="normal" font="default" size="100%">30</style></volume><pages><style face="normal" font="default" size="100%">129-135</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">H. J. Kim</style></author><author><style face="normal" font="default" size="100%">L. H. Cox</style></author><author><style face="normal" font="default" size="100%">Q. Wang</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multiple imputation of missing or faulty values under linear constraints</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Business Economic Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><publisher><style face="normal" font="default" size="100%">American Statistical Association</style></publisher><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">375-386</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sedransk, N.</style></author><author><style face="normal" font="default" size="100%">Leu, D.</style></author><author><style face="normal" font="default" size="100%">Forzani, E.</style></author><author><style face="normal" font="default" size="100%">Burlingame, C.</style></author><author><style face="normal" font="default" size="100%">Kulikowich, J.</style></author><author><style face="normal" font="default" size="100%">Coiro, J.</style></author><author><style face="normal" font="default" size="100%">Kennedy, C.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Neuman, S. B.</style></author><author><style face="normal" font="default" size="100%">Gambrell, L.B.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">The New Literacies of Online Research and Comprehension: Assessing and Preparing Students for the 21st Century with Common Core State Standards</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><publisher><style face="normal" font="default" size="100%">International Reading Association</style></publisher><pages><style face="normal" font="default" size="100%">to appear</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">to appear</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">H. J. Kim</style></author><author><style face="normal" font="default" size="100%">Karr Alan F</style></author><author><style face="normal" font="default" size="100%">L. H. Cox</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">Q. Wang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Simultaneous Edit-Imputation for Continuous Microdata</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><number><style face="normal" font="default" size="100%">189</style></number><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">S. K. Kinney</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">J. Miranda</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SynLBD 2.0: Improving the Synthetic Longitudinal Business Database</style></title><secondary-title><style face="normal" font="default" size="100%">Statistical Journal of the International Association for Official Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><volume><style face="normal" font="default" size="100%">30</style></volume><pages><style face="normal" font="default" size="100%">129-135</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Why data availability is such a hard problem</style></title><secondary-title><style face="normal" font="default" size="100%">Statistical Journal of the International Association for Official Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2014</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">30</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">101</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhang K</style></author><author><style face="normal" font="default" size="100%">Hughes-Oliver JM</style></author><author><style face="normal" font="default" size="100%">Young SS</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of high-dimensional structure-activity screening datasets using the optimal bit string Tree</style></title><secondary-title><style face="normal" font="default" size="100%">Technomet</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Classification</style></keyword><keyword><style  face="normal" font="default" size="100%">Drug discovery</style></keyword><keyword><style  face="normal" font="default" size="100%">High throughput screening</style></keyword><keyword><style  face="normal" font="default" size="100%">Prediction</style></keyword><keyword><style  face="normal" font="default" size="100%">QSAR</style></keyword><keyword><style  face="normal" font="default" size="100%">Simulated annealing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><volume><style face="normal" font="default" size="100%">55</style></volume><pages><style face="normal" font="default" size="100%">161-173</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We propose a new classification method called the Optimal Bit String Tree (OBSTree) to identify quantitative structure-activity relationships (QSARs). The method introduces the concept of a chromosome to describe the presence/absence context of a combination of descriptors. A descriptor set and its optimal chromosome form the splitting variable. A new stochastic searching scheme that contains a weighted sampling scheme, simulated annealing, and a trimming procedure optimizes the choice of splitting variable. Simulation studies and an application to screening monoamine oxidase inhibitors show that OBSTree is advantageous in accurately and effectively identifying QSAR rules and finding different classes of active compounds. Details of the algorithm, SAS code, and simulated and real datasets are available online as supplementary materials.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">I. A. Carrillo</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Combining cohorts in longitudinal surveys</style></title><secondary-title><style face="normal" font="default" size="100%">Survey Methodology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Joint-randomization inference</style></keyword><keyword><style  face="normal" font="default" size="100%">Multi-cohort longitudinal surveys</style></keyword><keyword><style  face="normal" font="default" size="100%">Replication variance estimation</style></keyword><keyword><style  face="normal" font="default" size="100%">Rotating panel surveys</style></keyword><keyword><style  face="normal" font="default" size="100%">Superpopulation parameters</style></keyword><keyword><style  face="normal" font="default" size="100%">Weighted Generalized Estimating Equations</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">149-182</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A question that commonly arises in longitudinal surveys is the issue of how to combine differing cohorts of the survey. In this paper we present a novel method for combining different cohorts, and using all available data, in a longitudinal survey to estimate parameters of a semiparametric model, which relates the response variable to a set of covariates. The procedure builds upon the Weighted Generalized Estimation Equation method for handling missing waves in longitudinal studies. Our method is set up under a joint-randomization frame work for estimation of model parameters, which takes into account the superpopulation model as well as the survey design randomization. We also propose a design-based, and a joint-randomization, variance estimation method. To illustrate the methodology we apply it to the Survey of Doctorate Recipients, conducted by the U.S. National Science Foundation&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">Z. He</style></author><author><style face="normal" font="default" size="100%">M. P. Cohen</style></author><author><style face="normal" font="default" size="100%">D. Battle</style></author><author><style face="normal" font="default" size="100%">D. L. Achorn</style></author><author><style face="normal" font="default" size="100%">A. D. McKay</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Construction of replicate weights for Project TALENT</style></title><secondary-title><style face="normal" font="default" size="100%">JSM Proceedings, Section on Survey Research Methods 2013</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Abbatiello, S.</style></author><author><style face="normal" font="default" size="100%">Feng, X.</style></author><author><style face="normal" font="default" size="100%">Sedransk, N.</style></author><author><style face="normal" font="default" size="100%">Mani, DR</style></author><author><style face="normal" font="default" size="100%">Schilling, B</style></author><author><style face="normal" font="default" size="100%">Maclean, B</style></author><author><style face="normal" font="default" size="100%">Zimmerman, LJ</style></author><author><style face="normal" font="default" size="100%">Cusack, MP</style></author><author><style face="normal" font="default" size="100%">Hall, SC</style></author><author><style face="normal" font="default" size="100%">Addona, T</style></author><author><style face="normal" font="default" size="100%">Allen, S</style></author><author><style face="normal" font="default" size="100%">Dodder, NG</style></author><author><style face="normal" font="default" size="100%">Ghosh, M</style></author><author><style face="normal" font="default" size="100%">Held, JM</style></author><author><style face="normal" font="default" size="100%">Hedrick, V</style></author><author><style face="normal" font="default" size="100%">Inerowicz, HD</style></author><author><style face="normal" font="default" size="100%">Jackson, A</style></author><author><style face="normal" font="default" size="100%">Keshishian, H</style></author><author><style face="normal" font="default" size="100%">Kim, JW</style></author><author><style face="normal" font="default" size="100%">Lyssand, JS</style></author><author><style face="normal" font="default" size="100%">Riley, CP</style></author><author><style face="normal" font="default" size="100%">Rudnick, P</style></author><author><style face="normal" font="default" size="100%">Sadowski, P</style></author><author><style face="normal" font="default" size="100%">Shaddox, K</style></author><author><style face="normal" font="default" size="100%">Smith, D</style></author><author><style face="normal" font="default" size="100%">Tomazela, D</style></author><author><style face="normal" font="default" size="100%">Wahlander, A</style></author><author><style face="normal" font="default" size="100%">Waldemarson, S</style></author><author><style face="normal" font="default" size="100%">Whitwell, CA</style></author><author><style face="normal" font="default" size="100%">You, J</style></author><author><style face="normal" font="default" size="100%">Zhang, S</style></author><author><style face="normal" font="default" size="100%">Kinsinger, CR</style></author><author><style face="normal" font="default" size="100%">Mesri, M</style></author><author><style face="normal" font="default" size="100%">Rodriguez, H</style></author><author><style face="normal" font="default" size="100%">Borchers, CH</style></author><author><style face="normal" font="default" size="100%">Buck, C</style></author><author><style face="normal" font="default" size="100%">Fisher, SJ</style></author><author><style face="normal" font="default" size="100%">Gibson, BW</style></author><author><style face="normal" font="default" size="100%">Liebler, D</style></author><author><style face="normal" font="default" size="100%">Maccoss, M</style></author><author><style face="normal" font="default" size="100%">Neubert, TA</style></author><author><style face="normal" font="default" size="100%">Paulovich, A</style></author><author><style face="normal" font="default" size="100%">Regnier, F</style></author><author><style face="normal" font="default" size="100%">Skates, SJ</style></author><author><style face="normal" font="default" size="100%">Tempst, P</style></author><author><style face="normal" font="default" size="100%">Wang, M</style></author><author><style face="normal" font="default" size="100%">Carr, SA</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Design, Implementation and Multisite Evaluation of a System Suitability Protocol for the Quantitative Assessment of Instrument Performance in Liquid Chromatography-Multiple Reaction Monitoring-MS (LC-MRM-MS)</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular and Cellular Proteomics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">2623-2639</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation &amp;lt;0.15, peak width coefficient of variation &amp;lt;0.15, standard deviation of RT &amp;lt;0.15 min (9 s), and the RT drift &amp;lt;0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Discussion of five papers on “Systems and architectures for high-quality statistics production</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Official Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">29</style></volume><pages><style face="normal" font="default" size="100%">157-163</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">National Institute of Statistical Sciences (US)</style></title><secondary-title><style face="normal" font="default" size="100%">Encyclopedia of Environmetrics, second edition</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><publisher><style face="normal" font="default" size="100%">Wiley, Chichester</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Isukapati, Isaac Kumar</style></author><author><style face="normal" font="default" size="100%">List, George F.</style></author><author><style face="normal" font="default" size="100%">Williams, Billy M</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Synthesizing route travel time distributions from segment travel time distributions</style></title><secondary-title><style face="normal" font="default" size="100%">Trans. Res. Rec.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2013</style></date></pub-dates></dates><pages><style face="normal" font="default" size="100%">71–81</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">D. L. Banks</style></author><author><style face="normal" font="default" size="100%">G. Datta</style></author><author><style face="normal" font="default" size="100%">J. Lynch</style></author><author><style face="normal" font="default" size="100%">J. Niemi</style></author><author><style face="normal" font="default" size="100%">F. Vera</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bayesian CAR models for syndromic surveillance on multiple data streams: Theory and practice</style></title><secondary-title><style face="normal" font="default" size="100%">Information Fusion</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bayes</style></keyword><keyword><style  face="normal" font="default" size="100%">CAR models</style></keyword><keyword><style  face="normal" font="default" size="100%">Gibbs distribution</style></keyword><keyword><style  face="normal" font="default" size="100%">Markov random field</style></keyword><keyword><style  face="normal" font="default" size="100%">Syndromic surveillance</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.inffus.2009.10.005</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">105–116</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Syndromic surveillance has, so far, considered only simple models for Bayesian inference. This paper details the methodology for a serious, scalable solution to the problem of combining symptom data from a network of US hospitals for early detection of disease outbreaks. The approach requires high-end Bayesian modeling and significant computation, but the strategy described in this paper appears to be feasible and offers attractive advantages over the methods that are currently used in this area. The method is illustrated by application to ten quarters worth of data on opioid drug abuse surveillance from 636 reporting centers, and then compared to two other syndromic surveillance methods using simulation to create known signal in the drug abuse database.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zou, Jian</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Banks, David</style></author><author><style face="normal" font="default" size="100%">Heaton, Matthew J.</style></author><author><style face="normal" font="default" size="100%">Datta, Gauri</style></author><author><style face="normal" font="default" size="100%">Lynch, James</style></author><author><style face="normal" font="default" size="100%">Vera, Francisco</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bayesian methodology for the analysis of spatial temporal surveillance data</style></title><secondary-title><style face="normal" font="default" size="100%">Statistical Analysis and Data Mining</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">conditional autoregressive process</style></keyword><keyword><style  face="normal" font="default" size="100%">Markov random field</style></keyword><keyword><style  face="normal" font="default" size="100%">spatial statistics</style></keyword><keyword><style  face="normal" font="default" size="100%">spatio-temporal</style></keyword><keyword><style  face="normal" font="default" size="100%">Syndromic surveillance</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1002/sam.10142</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><publisher><style face="normal" font="default" size="100%">Wiley Subscription Services, Inc., A Wiley Company</style></publisher><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">194–204</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Early and accurate detection of outbreaks is one of the most important objectives of syndromic surveillance systems. We propose a general Bayesian framework for syndromic surveillance systems. The methodology incorporates Gaussian Markov random field (GMRF) and spatio-temporal conditional autoregressive (CAR) modeling. By contrast, most previous approaches have been based on only spatial or time series models. The model has appealing probabilistic representations as well as attractive statistical properties. Based on extensive simulation studies, the model is capable of capturing outbreaks rapidly, while still limiting false positives. Â© 2012 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 5: 194â€“204, 2012&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hughes-Oliver JM</style></author><author><style face="normal" font="default" size="100%">Brooks A</style></author><author><style face="normal" font="default" size="100%">Welch W</style></author><author><style face="normal" font="default" size="100%">Khaldei MG</style></author><author><style face="normal" font="default" size="100%">Hawkins DM</style></author><author><style face="normal" font="default" size="100%">Young SS</style></author><author><style face="normal" font="default" size="100%">Patil K</style></author><author><style face="normal" font="default" size="100%">Howell GW</style></author><author><style face="normal" font="default" size="100%">Ng RT</style></author><author><style face="normal" font="default" size="100%">Chu MT</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ChemModLab: A web-based cheminromates modeling laboratory</style></title><secondary-title><style face="normal" font="default" size="100%">Cheminformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">61-81</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;ChemModLab, written by the ECCR @ NCSU consortium under NIH support, is a toolbox for fitting and assessing quantitative structure-activity relationships (QSARs). Its elements are: a cheminformatic front end used to supply molecular descriptors for use in modeling; a set of methods for fitting models; and methods for validating the resulting model. Compounds may be input as structures from which standard descriptors will be calculated using the freely available cheminformatic front end PowerMV; PowerMV also supports compound visualization. In addition, the user can directly input their own choices of descriptors, so the capability for comparing descriptors is effectively unlimited. The statistical methodologies comprise a comprehensive collection of approaches whose validity and utility have been accepted by experts in the fields. As far as possible, these tools are implemented in open-source software linked into the flexible R platform, giving the user the capability of applying many different QSAR modeling methods in a seamless way. As promising new QSAR methodologies emerge from the statistical and data-mining communities, they will be incorporated in the laboratory. The web site also incorporates links to public-domain data sets that can be used as test cases for proposed new modeling methods. The capabilities of ChemModLab are illustrated using a variety of biological responses, with different modeling methodologies being applied to each. These show clear differences in quality of the fitted QSAR model, and in computational requirements. The laboratory is web-based, and use is free. Researchers with new assay data, a new descriptor set, or a new modeling method may readily build QSAR models and benchmark their results against other findings. Users may also examine the diversity of the molecules identified by a QSAR model. Moreover, users have the choice of placing their data sets in a public area to facilitate communication with other researchers; or can keep them hidden to preserve confidentiality.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kulikowich, J.M.</style></author><author><style face="normal" font="default" size="100%">Sedransk, N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Current and emerging design and data analysis approaches</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><publisher><style face="normal" font="default" size="100%">APA Handbook of Educational Psychology, American Psychological Association</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Discussion on statistical use of administrative data: old and new challenges</style></title><secondary-title><style face="normal" font="default" size="100%">Statist. Neerlandica</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">66</style></volume><pages><style face="normal" font="default" size="100%">80-84</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">G. F. List</style></author><author><style face="normal" font="default" size="100%">B. M. Williams</style></author><author><style face="normal" font="default" size="100%">N. M. Rouphail</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Forging an understanding of travel time reliability for freeway and arterial networks</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 2012 International Symposium on Transportation Network Reliability (INSTR)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">S. K. Kinney</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Inferentially Valid, Partially Synthetic Datasets: Generating from Predictive Distributions Not Necessary</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Official Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">1-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">4</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. J. Heaton</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">J. Zou</style></author><author><style face="normal" font="default" size="100%">D. L. Banks</style></author><author><style face="normal" font="default" size="100%">G. Datta</style></author><author><style face="normal" font="default" size="100%">J. Lynch</style></author><author><style face="normal" font="default" size="100%">F. Vera</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A spatio-temporal absorbing state model for disease and syndromic surveillance</style></title><secondary-title><style face="normal" font="default" size="100%">Statistics in Medicine</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><number><style face="normal" font="default" size="100%">19</style></number><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">2123-2136</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Reliable surveillance models are an important tool in public health because they aid in mitigating disease outbreaks, identify where and when disease outbreaks occur, and predict future occurrences. Although many statistical models have been devised for surveillance purposes, none are able to simultaneously achieve the important practical goals of good sensitivity and specificity, proper use of covariate information, inclusion of spatio-temporal dynamics, and transparent support to decision-makers. In an effort to achieve these goals, this paper proposes a spatio-temporal conditional autoregressive hidden Markov model with an absorbing state. The model performs well in both a large simulation study and in an application to influenza/pneumonia fatality data.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">L. H. Cox</style></author><author><style face="normal" font="default" size="100%">S. K. Kinney</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The World’s Simplest Survey Microsimulator (WSSM)</style></title><secondary-title><style face="normal" font="default" size="100%">The World’s Simplest Survey Microsimulator (WSSM)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.fcsm.gov/12papers/Karr_2012FCSM_II-A.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nell Sedransk</style></author><author><style face="normal" font="default" size="100%">Lawrence H. Cox</style></author><author><style face="normal" font="default" size="100%">Deborah Nolan</style></author><author><style face="normal" font="default" size="100%">Keith Soper</style></author><author><style face="normal" font="default" size="100%">Cliff Spiegelman</style></author><author><style face="normal" font="default" size="100%">Linda J. Young</style></author><author><style face="normal" font="default" size="100%">Katrina L. Kelner</style></author><author><style face="normal" font="default" size="100%">Robert A. Moffitt</style></author><author><style face="normal" font="default" size="100%">Ani Thakar</style></author><author><style face="normal" font="default" size="100%">Jordan Raddick</style></author><author><style face="normal" font="default" size="100%">Edward J. Ungvarsky</style></author><author><style face="normal" font="default" size="100%">Richard W. Carlson</style></author><author><style face="normal" font="default" size="100%">Rolf Apweiler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Make research data public? - Not always so simple: A Dialogue for statisticians and science editors</style></title><secondary-title><style face="normal" font="default" size="100%">Statistical Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">41-50</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Putting data into the public domain is not the same thing as making those data accessible for intelligent analysis. A distinguished group of editors and experts who were already engaged in one way or another with the issues inherent in making research data public came together with statisticians to initiate a dialogue about policies and practicalities of requiring published research to be accompanied by publication of the research data. This dialogue carried beyond the broad issues of the advisability, the intellectual integrity, the scientific exigencies to the relevance of these issues to statistics as a discipline and the relevance of statistics, from inference to modeling to data exploration, to science and social science policies on these issues.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">National Institute of Statistical Sciences Configuration and Data Integration for Longitudinal Studies Technical Panel: Final Report (2011).</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><publisher><style face="normal" font="default" size="100%">US Department of Education, Institute of Education Sciences, NCES</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">607</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">National Institute of Statistical Sciences Data Confidentiality Technical Panel: Final Report</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><publisher><style face="normal" font="default" size="100%">US Department of Education, Institute of Education Sciences, NCES</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">608</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">S. K. Kinney</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Research access to restricted-use data</style></title><secondary-title><style face="normal" font="default" size="100%">Chance</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">41-45</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">L. H. Cox</style></author><author><style face="normal" font="default" size="100%">S. K. Kinney</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Risk-utility paradigms for statistical disclosure limitation: How to think, but not how to act (with discussion)</style></title><secondary-title><style face="normal" font="default" size="100%">International Statistical Review</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">79</style></volume><pages><style face="normal" font="default" size="100%">160-199</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Risk-utility formulations for problems of statistical disclosure limitation are now common. We argue that these approaches are powerful guides to official statistics agencies in regard to how to think about disclosure limitation problems, but that they fall short in essential ways from providing a sound basis for acting upon the problems. We illustrate this position in three specific contexts—transparency, tabular data and survey weights, with shorter consideration of two key emerging issues—longitudinal data and the use of administrative data to augment surveys.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pauley, L.</style></author><author><style face="normal" font="default" size="100%">Kulikowich, J.</style></author><author><style face="normal" font="default" size="100%">Sedransk, N.</style></author><author><style face="normal" font="default" size="100%">Engel, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Studying the Reliability and Validity of Test Scores for Mathematical and Spatial Reasoning Tasks for Engineering Students</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings, American Society for Engineering Education</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">S. K. Kinney</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">AP Reznek</style></author><author><style face="normal" font="default" size="100%">J Miranda</style></author><author><style face="normal" font="default" size="100%">R Jarmin</style></author><author><style face="normal" font="default" size="100%">JM Abowd</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Toward Unrestricted Public Use Business Microdata: The Synthetic Longitudinal Business Database</style></title><secondary-title><style face="normal" font="default" size="100%">International Statistical Review</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><volume><style face="normal" font="default" size="100%">79</style></volume><pages><style face="normal" font="default" size="100%"> 362-384</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stephan A. Carr</style></author><author><style face="normal" font="default" size="100%">Nell Sedransk.</style></author><author><style face="normal" font="default" size="100%">Henry Rodriguez</style></author><author><style face="normal" font="default" size="100%">Zivana Tezak</style></author><author><style face="normal" font="default" size="100%">Mehdi Mesri</style></author><author><style face="normal" font="default" size="100%">Daniel C. Liebler</style></author><author><style face="normal" font="default" size="100%">Susan J. Fisher</style></author><author><style face="normal" font="default" size="100%">Paul Tempst</style></author><author><style face="normal" font="default" size="100%">Tara Hiltke</style></author><author><style face="normal" font="default" size="100%">Larry G. Kessler</style></author><author><style face="normal" font="default" size="100%">Christopher R. Kinsinger</style></author><author><style face="normal" font="default" size="100%">Reena Philip</style></author><author><style face="normal" font="default" size="100%">David F. Ransohoff</style></author><author><style face="normal" font="default" size="100%">Steven J. Skates</style></author><author><style face="normal" font="default" size="100%">Fred E. Regnier</style></author><author><style face="normal" font="default" size="100%">N. Leigh Anderson</style></author><author><style face="normal" font="default" size="100%">Elizabeth Mansfield</style></author><author><style face="normal" font="default" size="100%">on behalf of the Workshop Participants</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analytical Validation of Proteomic-Based Multiplex Assays: A Workshop Report by the NCI-FDA Interagency Oncology Task Force on Molecular Diagnostics</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Clinical Chemistry</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><volume><style face="normal" font="default" size="100%">56</style></volume><pages><style face="normal" font="default" size="100%">237-243</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Clinical proteomics has the potential to enable the early detection of cancer through the development of multiplex assays that can inform clinical decisions. However, there has been some uncertainty among translational researchers and developers as to the specific analytical measurement criteria needed to validate protein-based multiplex assays. To begin to address the causes of this uncertainty, a day-long workshop titled “Interagency Oncology Task Force Molecular Diagnostics Workshop” was held in which members of the proteomics and regulatory communities discussed many of the analytical evaluation issues that the field should address in development of protein-based multiplex assays for clinical use. This meeting report explores the issues raised at the workshop and details the recommendations that came out of the day’s discussions, such as a workshop summary discussing the analytical evaluation issues that specific proteomic technologies should address when seeking US Food and Drug Administration approval.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">S. H. Holan</style></author><author><style face="normal" font="default" size="100%">D. Toth</style></author><author><style face="normal" font="default" size="100%">M. A. R. Ferreira</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bayesian multiscale multiple imputation with implications to data confidentiality</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of American Statistical Association</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><number><style face="normal" font="default" size="100%">490</style></number><volume><style face="normal" font="default" size="100%">105</style></volume><pages><style face="normal" font="default" size="100%">564-577</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Many scientific, sociological, and economic applications present data that are collected on multiple scales of resolution. One particular form of multiscale data arises when data are aggregated across different scales both longitudinally and by economic sector. Frequently, such datasets experience missing observations in a manner that they can be accurately imputed, while respecting the constraints imposed by the multiscale nature of the data, using the method we propose known as Bayesian multiscale multiple imputation. Our approach couples dynamic linear models with a novel imputation step based on singular normal distribution theory. Although our method is of independent interest, one important implication of such methodology is its potential effect on confidential databases protected by means of cell suppression. In order to demonstrate the proposed methodology and to assess the effectiveness of disclosure practices in longitudinal databases, we conduct a large-scale empirical study using the U.S. Bureau of Labor Statistics Quarterly Census of Employment and Wages (QCEW). During the course of our empirical investigation it is determined that several of the predicted cells are within 1% accuracy, thus causing potential concerns for data confidentiality.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pauley, L.</style></author><author><style face="normal" font="default" size="100%">Kulikowich, J.M.</style></author><author><style face="normal" font="default" size="100%">Sedransk, N.</style></author><author><style face="normal" font="default" size="100%">Engel, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Constructing mathematical and spatial-reasoning measures for engineering students</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings, American Society for Engineering Education</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">S. K. Kinney</style></author><author><style face="normal" font="default" size="100%">J. F. Gonzalez, Jr.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data confidentiality—the next five years: Summary and guide to papers</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Privacy and Confidentiality</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">125-134</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">A. Oganian</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Masking methods that preserve positivity constraints in microdata</style></title><secondary-title><style face="normal" font="default" size="100%">J. Statist. Planning Inf.</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">constraints</style></keyword><keyword><style  face="normal" font="default" size="100%">Positivity</style></keyword><keyword><style  face="normal" font="default" size="100%">SDL method</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical disclosure limitation (SDL)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">141</style></volume><pages><style face="normal" font="default" size="100%">31-41</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Statistical agencies have conflicting obligations to protect confidential information provided by respondents to surveys or censuses and to make data available for research and planning activities. When the microdata themselves are to be released, in order to achieve these conflicting objectives, statistical agencies apply statistical disclosure limitation (SDL) methods to the data, such as noise addition, swapping or microaggregation. Some of these methods do not preserve important structure and constraints in the data, such as positivity of some attributes or inequality constraints between attributes. Failure to preserve constraints is not only problematic in terms of data utility, but also may increase disclosure risk. In this paper, we describe a method for SDL that preserves both positivity of attributes and the mean vector and covariance matrix of the original data. The basis of the method is to apply multiplicative noise with the proper, data-dependent covariance structure.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Preserving data utility via BART</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Statistical Planning Inf.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><number><style face="normal" font="default" size="100%">9</style></number><volume><style face="normal" font="default" size="100%">140</style></volume><pages><style face="normal" font="default" size="100%">2551-2561</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">X. Lin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Privacy-preserving maximum likelihood estimation for distributed data</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Privacy and Confidentiality</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">213-222</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sedransk, N.</style></author><author><style face="normal" font="default" size="100%">Kulikowich, J.M.</style></author><author><style face="normal" font="default" size="100%">Engel, R.</style></author><author><style face="normal" font="default" size="100%">X. Wang</style></author><author><style face="normal" font="default" size="100%">Gunning, P.</style></author><author><style face="normal" font="default" size="100%">Fleming, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Psychometric and Statistical Modeling for the Study of Retention and Graduation in Undergraduate Engineering</style></title><secondary-title><style face="normal" font="default" size="100%">Social Statistics and Higher Education Conference Volume</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Secure statistical analysis of distributed databases, emphasizing what we don’t know</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Privacy and Confidentiality</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">197-211</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">A. Oganyan</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">M.-J. Woo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Global measures of data utility for microdata masked for disclosure limitation</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Privacy and Confidentiality</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">111-124</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">NISS/NESSI Task Force on Full Population Estimates for NAEP</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><number><style face="normal" font="default" size="100%">172</style></number><publisher><style face="normal" font="default" size="100%">National Institute of Statistical Sciences</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">X. Lin</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Privacy-preserving analysis of vertically partitioned data using secure matrix products</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Official Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">25</style></volume><pages><style face="normal" font="default" size="100%">125-138</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The role of transparency in statistical disclosure limitation</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">December</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.46/2009/wp.41.e.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Bilbao, Spain</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">A. Oganyan</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Verification servers: enabling analysts to assess the quality of inferences from public use data</style></title><secondary-title><style face="normal" font="default" size="100%">Computational Statistics and Data Analysis</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">53</style></volume><pages><style face="normal" font="default" size="100%">1475-1482</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;To protect confidentiality, statistical agencies typically alter data before releasing them to the public. Ideally, although generally not done, the agency also provides a way for secondary data analysts to assess the quality of inferences obtained with the released data. Quality measures can help secondary data analysts to identify inaccurate conclusions resulting from the disclosure limitation procedures, as well as have confidence in accurate conclusions. We propose a framework for an interactive, web-based system that analysts can query for measures of inferential quality. As we illustrate, agencies seeking to build such systems must consider the additional disclosure risks from releasing quality measures. We suggest some avenues of research on limiting these risks.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Young SS</style></author><author><style face="normal" font="default" size="100%">Bang H</style></author><author><style face="normal" font="default" size="100%">Oktay K</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cereal-induced gender selection? Most likely a multiple testing false positive</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings - Royal Society B</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://rspb.royalsocietypublishing.org/content/276/1660/1211.full</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">276</style></volume><pages><style face="normal" font="default" size="100%">1211-1212</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">H. Chen</style></author><author><style face="normal" font="default" size="100%">L. Brandt</style></author><author><style face="normal" font="default" size="100%">V. Gregg</style></author><author><style face="normal" font="default" size="100%">R. Traunmüller</style></author><author><style face="normal" font="default" size="100%">S. Dawes</style></author><author><style face="normal" font="default" size="100%">E. Hovy</style></author><author><style face="normal" font="default" size="100%">A. Macintosh</style></author><author><style face="normal" font="default" size="100%">C. A. Larson</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Citizen access to government statistical information</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer US</style></publisher><pages><style face="normal" font="default" size="100%">503-529</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Modern electronic technologies have dramatically increased the volume of information collected and assembled by government agencies at all levels. This chapter describes digital government research aimed at keeping government data warehouses from turning into data cemeteries. The products of the research exploit modern electronic technologies in order to allow “ordinary citizens” and researchers access to government-assembled information. The goal is to help ensure that more data also means better and more useful data. Underlying the chapter are three tensions. The first is between comprehensiveness and understandability of information available to non-technically oriented “private citizens.” The second is between ensuring usefulness of detailed statistical information and protecting confidentiality of data subjects. The third tension is between the need to analyze “global” data sets and the reality that government data are distributed among both levels of government and agencies (typically, by the “domain” of data, such as education, health, or transportation).&lt;/p&gt;
</style></abstract><section><style face="normal" font="default" size="100%">25</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mi-ja Woo</style></author><author><style face="normal" font="default" size="100%">Jerome Reiter</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimation of propensity scores using generalized additive models</style></title><secondary-title><style face="normal" font="default" size="100%">Statisics in Medicine</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">3806-3816</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">H. T. Banks</style></author><author><style face="normal" font="default" size="100%">H. K. Nguyen</style></author><author><style face="normal" font="default" size="100%">J. R. Samuels, Jr.</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sensitivity to noise variance in a social network dynamics model</style></title><secondary-title><style face="normal" font="default" size="100%">Q. Applied Mathematics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">66</style></volume><pages><style face="normal" font="default" size="100%">233-247</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">J. Ghosh</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Secure computation with horizontally partitioned data using adaptive regression splines</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Computational Statistics and Data Analysis</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">August</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">12</style></number><volume><style face="normal" font="default" size="100%">51</style></volume><pages><style face="normal" font="default" size="100%">5813-5820</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;When several data owners possess data on different records but the same variables, known as horizontally partitioned data, the owners can improve statistical inferences by sharing their data with each other. Often, however, the owners are unwilling or unable to share because the data are confidential or proprietary. Secure computation protocols enable the owners to compute parameter estimates for some statistical models, including linear regressions, without sharing individual records’ data. A drawback to these techniques is that the model must be specified in advance of initiating the protocol, and the usual exploratory strategies for determining good-fitting models have limited usefulness since the individual records are not shared. In this paper, we present a protocol for secure adaptive regression splines that allows for flexible, semi-automatic regression modeling. This reduces the risk of model mis-specification inherent in secure computation settings. We illustrate the protocol with air pollution data.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">S. E. Fienberg</style></author><author><style face="normal" font="default" size="100%">Y. Nardi</style></author><author><style face="normal" font="default" size="100%">A. Slavkovic</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Secure logistic regression with distributed databases</style></title><secondary-title><style face="normal" font="default" size="100%">Bulletin of International Statistics Institute</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Murali Haran</style></author><author><style face="normal" font="default" size="100%">Alan Karr</style></author><author><style face="normal" font="default" size="100%">Michael Last</style></author><author><style face="normal" font="default" size="100%">Alessandro Orso</style></author><author><style face="normal" font="default" size="100%">Adam A. Porter</style></author><author><style face="normal" font="default" size="100%">Ashish Sanil</style></author><author><style face="normal" font="default" size="100%">Sandro Fouché</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Techniques for classifying executions of deployed software to support software engineering tasks</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE TRANSACTIONS ON SOFTWARE ENGINEERING</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">33</style></volume><pages><style face="normal" font="default" size="100%">287-304</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">A. Oganyan</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">J. Domingo–Ferrer</style></author><author><style face="normal" font="default" size="100%">L. Franconi</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Combinations of SDC methods for microdata protection</style></title><secondary-title><style face="normal" font="default" size="100%">Privacy in Statistical Databases: CENEX–SDC Project International Conference, PSD 2006 Rome, Italy, December 13–15, 2006 Proceedings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">December</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author><author><style face="normal" font="default" size="100%">David L. Banks</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data quality: A statistical perspective</style></title><secondary-title><style face="normal" font="default" size="100%">Statistical Methodology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">137–173</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">C. N. Kohnen</style></author><author><style face="normal" font="default" size="100%">A. Oganyan</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A framework for evaluating the utility of data altered to protect confidentiality</style></title><secondary-title><style face="normal" font="default" size="100%">The American Statistician</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">60</style></volume><pages><style face="normal" font="default" size="100%">224-232</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Fulp, WJ</style></author><author><style face="normal" font="default" size="100%">F. Vera</style></author><author><style face="normal" font="default" size="100%">Young, S.S.</style></author><author><style face="normal" font="default" size="100%">X. Lin</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Secure, privacy-preserving analysis of distributed databases</style></title><secondary-title><style face="normal" font="default" size="100%">Technometrics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">48</style></volume><pages><style face="normal" font="default" size="100%">133-143</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;There is clear value, in both industrial and government settings, derived from performing statistical analyses that, in effect, integrate data in multiple, distributed databases. However, the barriers to actually integrating the data can be substantial or even insurmountable. Corporations may be unwilling to share proprietary databases such as chemical databases held by pharmaceutical manufacturers, government agencies are subject to laws protecting confidentiality of data subjects, and even the sheer volume of the data may preclude actual data integration. In this paper, we show how tools from modern information technology?specifically, secure multiparty computation and networking?can be used to perform statistically valid analyses of distributed databases. The common characteristic of the methods we describe is that the owners share sufficient statistics computed on the local databases in a way that protects each owner from the others. That is, while each owner can calculate the ?complement ? of its contribution to the analysis, it cannot discern which other owners contributed what to that complement. Our focus is on horizontally partitioned data: the data records rather than the data attributes are spread among the owners. We present protocols for secure regression, contingency tables, maximum likelihood and Bayesian analysis. For low-risk situations, we describe a secure data integration protocol that integrates the databases but prevents owners from learning the source of data records other than their own. Finally, we outline three current research directions: a software system implementing the protocols, secure EM algorithms, and partially trusted third parties, which reduce incentives to owners not to be honest.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Remlinger KS</style></author><author><style face="normal" font="default" size="100%">Hughes-Oliver JM</style></author><author><style face="normal" font="default" size="100%">Young SS</style></author><author><style face="normal" font="default" size="100%">Lam RL</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Statistical design of pools using optimal coverage and minimal collision</style></title><secondary-title><style face="normal" font="default" size="100%">Technom</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Pharmaceutical industry</style></keyword><keyword><style  face="normal" font="default" size="100%">Pooled data</style></keyword><keyword><style  face="normal" font="default" size="100%">Pooling</style></keyword><keyword><style  face="normal" font="default" size="100%">Screening</style></keyword><keyword><style  face="normal" font="default" size="100%">Throughput</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">48</style></volume><pages><style face="normal" font="default" size="100%">133-143</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The screening of large chemical libraries to identify new compounds can be simplified by testing compounds in pools. Two criteria for designing pools are considered: optimal coverage of the chemical space and minimal collision between compounds. Four pooling designs are applied to a public database and evaluated by determining how well the design criteria are met and whether the methods are able to find diverse active compounds. While one pool was outstanding, all designed pools outperformed randomly designed pools.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">M. Last</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Survey Costs: Workshop Report and White Paper</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><number><style face="normal" font="default" size="100%">161</style></number><publisher><style face="normal" font="default" size="100%">National Institute of Statistical Sciences</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">M. Haran</style></author><author><style face="normal" font="default" size="100%">A. A. Porter</style></author><author><style face="normal" font="default" size="100%">A. Orso</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Applying classification techniques to remotely-collected program execution data</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. ACM SIGSOFT Symposium Foundations of Software Engineering 2005</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">New York</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">J. Feng</style></author><author><style face="normal" font="default" size="100%">X. Lin</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author><author><style face="normal" font="default" size="100%">Young, S.S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data dissemination and disclosure limitation in a world without microdata: A risk-utility framework for remote access analysis servers</style></title><secondary-title><style face="normal" font="default" size="100%">Statistical Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">163-177</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data quality and data confidentiality for microdata: implications and strategies</style></title><secondary-title><style face="normal" font="default" size="100%">Bull. International Statistical Inst., 55th Session</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Shanti Gomatam</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data Swapping as a Decision Problem</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Official Statistics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">categorical data</style></keyword><keyword><style  face="normal" font="default" size="100%">data confidentiality</style></keyword><keyword><style  face="normal" font="default" size="100%">Data swapping</style></keyword><keyword><style  face="normal" font="default" size="100%">data utility</style></keyword><keyword><style  face="normal" font="default" size="100%">disclosure risk</style></keyword><keyword><style  face="normal" font="default" size="100%">risk-utility frontier</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">635–655</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We construct a decision-theoretic formulation of data swapping in which quantitative measures of disclosure risk and data utility are employed to select one release from a possibly large set of candidates. The decision variables are the swap rate, swap attribute(s) and, possibly, constraints on the unswapped attributes. Risk–utility frontiers, consisting of those candidates not dominated in (risk, utility) space by any other candidate, are a principal tool for reducing the scale of the decision problem. Multiple measures of disclosure risk and data utility, including utility measures based directly on use of the swapped data for statistical inference, are introduced. Their behavior and resulting insights into the decision problem are illustrated using data from the U.S. Current Population Survey, the well-studied “Czech auto worker data” and data on schools and administrators generated by the U.S. National Center for Education Statistics.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Discussion of ‘The impact of technology on the scientific method&#039; by S. Keller–McNulty, A. G.Wilson and G. Wilson</style></title><secondary-title><style face="normal" font="default" size="100%">Chance</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">1</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. A. Porter</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Distributed performance testing using statistical modeling</style></title><secondary-title><style face="normal" font="default" size="100%">ICSE 2005 Workshop on Advances in Model-Based Software Testing (A-MOST)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">National Institute of Statistical Sciences/Education Statistics Services Institute Task Force on Graduation, Completion and Dropout Indicators: Final Report</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">November</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">US Department of Education, Institute of Education Sciences, NCES</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Jun Feng</style></author><author><style face="normal" font="default" size="100%">Xiaodong Lin</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author><author><style face="normal" font="default" size="100%">S. Stanley Young</style></author><author><style face="normal" font="default" size="100%">Jerome P. Reiter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Secure analysis of distributed chemical databases without data integration</style></title><secondary-title><style face="normal" font="default" size="100%">J. Computer-Aided Molecular Design</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">November</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">9-10</style></number><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">739-747</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Xiaodong Lin</style></author><author><style face="normal" font="default" size="100%">Xiaodong Lin</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author><author><style face="normal" font="default" size="100%">Jerome P. Reiter</style></author><author><style face="normal" font="default" size="100%">Jerome P. Reiter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Secure Regression on Distributed Databases</style></title><secondary-title><style face="normal" font="default" size="100%">J. Computational and Graphical Statist</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">263–279</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Xiaodong Lin</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author><author><style face="normal" font="default" size="100%">Jerome P. Reiter</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">D. Olwell</style></author><author><style face="normal" font="default" size="100%">A. G.Wilson</style></author><author><style face="normal" font="default" size="100%">G. Wilson</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Secure statistical analysis of distributed databases using partially trusted third parties. Manuscript in preparation</style></title><secondary-title><style face="normal" font="default" size="100%">In Statistical Methods in Counterterrorism: Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer–Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">New York</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Title IX Data Collection: Technical Manual for Developing the User’s Guide</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><number><style face="normal" font="default" size="100%">150</style></number><publisher><style face="normal" font="default" size="100%">National Institute of Statistical Sciences</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">X. Lin</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of integrated data without data integration</style></title><secondary-title><style face="normal" font="default" size="100%">Chance</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">26-29</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data confidentiality, data quality and data integration for federal databases</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. dg.o 2004, National Conference on Digital Government Research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><pages><style face="normal" font="default" size="100%">91-92</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. Haran</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Model for Relating Browsing Behavior to Site Design on the World Wide Web</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of JSM 2004</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">August</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">American Statistical Association</style></publisher><pub-location><style face="normal" font="default" size="100%">Alexandria, VA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">X. Lin</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Privacy preserving regression modelling via distributed computation</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><pages><style face="normal" font="default" size="100%">677-682</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">X. Lin</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Regression on distributed databases via secure multi-party computation</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. dg.o 2004, National Conference on Digital Government Research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><pages><style face="normal" font="default" size="100%">405-406</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">C. N. Kohnen</style></author><author><style face="normal" font="default" size="100%">X. Lin</style></author><author><style face="normal" font="default" size="100%">J. P. Reiter</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Secure regression for vertically partitioned, partially overlapping data</style></title><secondary-title><style face="normal" font="default" size="100%">ASA Proceedings 2004</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">S. Gomatam</style></author><author><style face="normal" font="default" size="100%">C. Liu</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Data swapping: A risk–utility framework and Web service implementation</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. dg.o 2003, National Conference on Digital Government Research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><publisher><style face="normal" font="default" size="100%">Digital Government Research Center</style></publisher><pages><style face="normal" font="default" size="100%">245-248</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ashish Sanil</style></author><author><style face="normal" font="default" size="100%">Shanti Gomatam</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">NISS WebSwap: A Web Service for Data Swapping</style></title><secondary-title><style face="normal" font="default" size="100%">J. Statist. Software</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">2003</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Adrian Dobra</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Preserving confidentiality of high-dimensional tabular data: Statistical and computational issues</style></title><secondary-title><style face="normal" font="default" size="100%">STATISTICS AND COMPUTING</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">363–370</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Adrian Dobra</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Table servers protect confidentiality in tabular data releases</style></title><secondary-title><style face="normal" font="default" size="100%">Comm. ACM</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">46</style></volume><pages><style face="normal" font="default" size="100%">57–58</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">J. Lee</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author><author><style face="normal" font="default" size="100%">J. Hernandez</style></author><author><style face="normal" font="default" size="100%">S. Karimi</style></author><author><style face="normal" font="default" size="100%">K. Litwin</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">E. Elmagarmid</style></author><author><style face="normal" font="default" size="100%">W. M. McIver</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Advances in Digital Government</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><publisher><style face="normal" font="default" size="100%">Kluwer</style></publisher><pub-location><style face="normal" font="default" size="100%">Boston</style></pub-location><pages><style face="normal" font="default" size="100%">181-196</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4020-7067-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The Internet provides an efficient mechanism for Federal agencies to distribute their data to the public. However, it is imperative that such data servers have built-in mechanisms to ensure that confidentiality of the data, and the privacy of individuals or establishments represented in the data, are not violated. We describe a prototype dissemination system developed for the National Agricultural Statistics Service that uses aggregation of adjacent geographical units as a confidentiality-preserving technique. We also outline a Bayesian approach to statistical analysis of the aggregated data.&lt;/p&gt;
</style></abstract><section><style face="normal" font="default" size="100%">Web-based systems that disseminate information from data but preserve confidentiality</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bruce E Ankenman</style></author><author><style face="normal" font="default" size="100%">Hui Liu</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Jeffrey D. Picka</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Experimental designs for estimating a response surface and variance components</style></title><secondary-title><style face="normal" font="default" size="100%">Technometrics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">44</style></volume><pages><style face="normal" font="default" size="100%">45-54</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M.J. Bayarri</style></author><author><style face="normal" font="default" size="100%">J. Berger</style></author><author><style face="normal" font="default" size="100%">D. Higdon</style></author><author><style face="normal" font="default" size="100%">M. Kottas</style></author><author><style face="normal" font="default" size="100%">R. Paulo</style></author><author><style face="normal" font="default" size="100%">J. Sacks</style></author><author><style face="normal" font="default" size="100%">J. Cafeo</style></author><author><style face="normal" font="default" size="100%">J. Cavendish</style></author><author><style face="normal" font="default" size="100%">C. Lin</style></author><author><style face="normal" font="default" size="100%">J. Tu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Framework for Validating Computer Models</style></title><secondary-title><style face="normal" font="default" size="100%">Workshop on Foundations for Modeling and Simulation</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Society for Computer Simulation</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">National Institute of Statistical Sciences (US)</style></title><secondary-title><style face="normal" font="default" size="100%">Encyclopedia of Environmetrics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><publisher><style face="normal" font="default" size="100%">Wiley, Chichester</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">A. Dobra</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimal tabular releases from confidential data</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. dgo.2002, National Conference on Digital Government Research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Julie Rapoport Corina–Maria</style></author><author><style face="normal" font="default" size="100%">Surendra P. Shah</style></author><author><style face="normal" font="default" size="100%">Bruce Ankenman</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Permeability of Cracked Steel Fiber–Reinforced Concrete</style></title><secondary-title><style face="normal" font="default" size="100%">ASCE J. Materials</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">355–358</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This research explores the relationship between permeability and crack width in cracked, steel fiber–reinforced concrete. In addition, it inspects the influence of steel fiber reinforcement on concrete permeability. The feedback–controlled splitting tension test (also known as the Brazilian test) is used to induce cracks of up to 500 microns (0.02in) in concrete specimens without reinforcement, and with steel fiber reinforcement volumes of both 0.5% and 1%. The cracks relax after induced cracking. The steel fibers decrease permeability of specimens with relaxed cracks larger than 100 microns. Keywords: permeability, fiber-reinforced concrete, steel fibers 1 NSF Center for Advanced Cement–Based Materials, Northwestern University, 2145 Sheridan Rd., Evanston, IL, 60208–4400, USA 2 Saint Gobain Technical Fabrics, P. Box 728, St. Catharines, Ontario, L2R-6Y3, Canada 3 Department of Industrial Engineering and Management Science, Northwestern University, 2145 Sheridan Rd., Evanston, IL.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Adrian Dobra</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author><author><style face="normal" font="default" size="100%">Stephen E. Fienberg</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Software Systems for Tabular Data Releases</style></title><secondary-title><style face="normal" font="default" size="100%">Int. Journal of Uncertainty, Fuzziness and Knowledge Based Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">529-544</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Claudia Tebaldi</style></author><author><style face="normal" font="default" size="100%">Mike West</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Statistical Analyses of Freeway Traffic Flows</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Forecasting</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">39–68</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">T.L. Graves</style></author><author><style face="normal" font="default" size="100%">A. Mockus</style></author><author><style face="normal" font="default" size="100%">P. Schuster</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Variability of travel times on arterial streets: effects of signals and volume</style></title><secondary-title><style face="normal" font="default" size="100%">Transportation Research Record C</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">000-000</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">S. G. Eick</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Visual Scalability</style></title><secondary-title><style face="normal" font="default" size="100%">Journal Comp. Graphical Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">22-43</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stephen G. Eick</style></author><author><style face="normal" font="default" size="100%">Paul Schuster</style></author><author><style face="normal" font="default" size="100%">Audris Mockus</style></author><author><style face="normal" font="default" size="100%">Todd L. Graves</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Visualizing Software Changes</style></title><secondary-title><style face="normal" font="default" size="100%">INTERACTIONS</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">29–31</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jaeyong Lee</style></author><author><style face="normal" font="default" size="100%">Christopher Holloman</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of aggregated data in survey sampling with application to fertilizer/pesticide usage surveys</style></title><secondary-title><style face="normal" font="default" size="100%">Res. Official Statist</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">11–6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In many cases, the public release of survey or census data at fine geographical resolution (for example, counties) may endanger the confidentiality of respondents. A strategy for such cases is to aggregate neighboring regions into larger units that satisfy confidentiality requirements. An aggregation procedure employed in a prototype system for the US National Agricultural Statistics Service is used as context to investigate the impact of aggregation on statistical properties of the data. We propose a Bayesian simulation approach for the analysis of such aggregated data. As a consequence, we are able to specify the type of additional information (such as certain sample sizes) that needs to be released in order to enable the user to perform meaningful analyses with the aggregated data.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">C.-M. Aldea</style></author><author><style face="normal" font="default" size="100%">J. Rapoport</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Combined effect of cracking and water permeability of fiber-reinforced concrete</style></title><secondary-title><style face="normal" font="default" size="100%">Concrete Under Severe Conditions, Proceedings of the Third International Conference on Concrete Under Severe Conditions</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><pages><style face="normal" font="default" size="100%">71?78</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan Karr</style></author><author><style face="normal" font="default" size="100%">William DuMouchel</style></author><author><style face="normal" font="default" size="100%">Wen-Hua Ju</style></author><author><style face="normal" font="default" size="100%">Martin Theus</style></author><author><style face="normal" font="default" size="100%">Yehuda Vardi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computer intrusion: detecting masqueraders</style></title><secondary-title><style face="normal" font="default" size="100%">Statistical Science</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Anomaly</style></keyword><keyword><style  face="normal" font="default" size="100%">Bayes</style></keyword><keyword><style  face="normal" font="default" size="100%">compression</style></keyword><keyword><style  face="normal" font="default" size="100%">computer security</style></keyword><keyword><style  face="normal" font="default" size="100%">high-orderMarkov</style></keyword><keyword><style  face="normal" font="default" size="100%">profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Unix</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">1-17</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Masqueraders in computer intrusion detection are people who use somebody else?s computer account. We investigate a number of statistical approaches for detecting masqueraders. To evaluate them, we collected UNIX command data from 50 users and then contaminated the data with masqueraders. The experiment was blinded. We show results from six methods, including two approaches from the computer science community.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">J. Hernandez</style></author><author><style face="normal" font="default" size="100%">S. Karimi</style></author><author><style face="normal" font="default" size="100%">J. Lee</style></author><author><style face="normal" font="default" size="100%">K. Litwin</style></author><author><style face="normal" font="default" size="100%">A. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Disseminating information but protecting confidentiality</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Computer</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">36?37</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stephen G. Eick</style></author><author><style face="normal" font="default" size="100%">Todd L. Graves</style></author><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">J. S. Marron</style></author><author><style face="normal" font="default" size="100%">Audris Mockus</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Does code decay? Assessing the evidence from change management data</style></title><secondary-title><style face="normal" font="default" size="100%">In IEEE Transactions on Software Engineering</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><pages><style face="normal" font="default" size="100%">1–12</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A central feature of the evolution of large software systems is that changeÐwhich is necessary to add new functionality, accommodate new hardware, and repair faultsÐbecomes increasingly difficult over time. In this paper, we approach this phenomenon, which we term code decay, scientifically and statistically. We define code decay and propose a number of measurements (code decay indices) on software and on the organizations that produce it, that serve as symptoms, risk factors, and predictors of decay. Using an unusually rich data set (the fifteen-plus year change history of the millions of lines of software for a telephone switching system), we find mixed, but on the whole persuasive, statistical evidence of code decay, which is corroborated by developers of the code. Suggestive indications that perfective maintenance can retard code decay are also discussed. Index TermsÐSoftware maintenance, metrics, statistical analysis, fault potential, span of changes, effort modeling.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Web-based systems that disseminate information but protect confidential data</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings dg.o 2001</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><publisher><style face="normal" font="default" size="100%">Digital Government Research Center</style></publisher><pages><style face="normal" font="default" size="100%">159?166</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan F. Karr</style></author><author><style face="normal" font="default" size="100%">Ashish P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Web-Based Systems that Disseminate Information but Protect Confidential Data</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Digital Government. Kluwer, Amserdam</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><publisher><style face="normal" font="default" size="100%">Kluwer</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author><author><style face="normal" font="default" size="100%">J. Sacks</style></author><author><style face="normal" font="default" size="100%">A. Elmagarmid</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Workshop Report: Affiliates Workshop on Data Quality</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><number><style face="normal" font="default" size="100%">117</style></number><publisher><style face="normal" font="default" size="100%">National Institute of Statistical Sciences</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">J. Lee</style></author><author><style face="normal" font="default" size="100%">A. P. Sanil</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Workshop Report: Workshop on Statistics and Information Technology</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><number><style face="normal" font="default" size="100%">118</style></number><publisher><style face="normal" font="default" size="100%">National Institute of Statiatical Sciences</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sun,Dongchu</style></author><author><style face="normal" font="default" size="100%">Tsuakawa, R. K.</style></author><author><style face="normal" font="default" size="100%">Kim, H.</style></author><author><style face="normal" font="default" size="100%">Z. He</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bayesian Analysis of Mortality Rates with Disease Maps</style></title><secondary-title><style face="normal" font="default" size="100%">Statistics in Medicine</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">2015-2035</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This article summarizes our research on estimation of age-specific and age-adjusted mortality rates for chronic obstructive pulmonary disease (COPD) for white males. Our objectives are more precise and informative displays (than previously available) of geographic variation of the age-specific mortality rates for COPD, and investigation of the relationships between the geographic variation in mortality rates and the corresponding variation in selected covariates. For a given age class, our estimates are displayed in a choropleth map of mean rates. We develop a variation map that identifies the geographical areas where inferences are reliable. Here, the variation is measured by considering a set of maps produced using samples from the posterior distribution of the population mortality rates. Finally, we describe the spatial patterns in the age-specific maps and relate these to patterns in potential explanatory covariates such as smoking rate, annual rainfall, population density, elevation, and measures of air quality.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">N. Raghavan</style></author><author><style face="normal" font="default" size="100%">R. Bell</style></author><author><style face="normal" font="default" size="100%">M. Schonlau</style></author><author><style face="normal" font="default" size="100%">D. Pregibon</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Defection detection: Using online activity profiles to predict ISP customer vulnerability</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><pages><style face="normal" font="default" size="100%">506?515</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">C.-M. Aldea</style></author><author><style face="normal" font="default" size="100%">M. Ghandehari</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimation of water flow through cracked concrete under load</style></title><secondary-title><style face="normal" font="default" size="100%">ACI Materials Journal</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">97</style></volume><pages><style face="normal" font="default" size="100%">567?575</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This research studied the relationship between cracking and water permeability of normal-strength concrete under load and compared the experimental results with theoretical models. A feedback-controlled wedge splitting test was used to generate width-controlled cracks. Speckle interferometry was used to record the cracking history. Water permeability of the loaded specimens was evaluated by a low-pressure water permeability test at the designed crack mouth opening displacements (CMODs). Water permeability results were compared with those previously obtained for unloaded specimens for which cracks were induced by a feedback-controlled splitting tension test. The experimental results indicate that water permeability of cracked material significantly increases with increasing crack width. The flow for the same cracking level is repeatable regardless of the procedure used for inducing the cracks. No direct relationship between water flow and crack length was observed, whereas clear relationships existed between CMOD or crack area and flow characteristics. Experimentally measured flow was compared with theoretical models of flow through cracked rocks with parallel walls and a correction factor accounting for the tortuosity of the crack was determined. Calculated flow through cracks induced by a wedge-splitting test provided an acceptable approximation of the measured flow.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">C.-M. Aldea</style></author><author><style face="normal" font="default" size="100%">J.D. Picka</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author><author><style face="normal" font="default" size="100%">S.S. Jaiswal</style></author><author><style face="normal" font="default" size="100%">T. Igusa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Experimental and statistical study of chloride permeability of cracked high strength concrete</style></title><secondary-title><style face="normal" font="default" size="100%">ASTM Cement, Concrete and Aggregates</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year><pub-dates><date><style  face="normal" font="default" size="100%">December</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">000-000</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Within any cast cylinder of concrete, the coarse aggregate will tend to be inhomogeneously distributed. This variability may arise as a result of segregation caused by gravity or as a result of the wall effect that is caused by the inability of the aggregate to penetrate the walls of the mold. Using methods from image analysis, stereology, and statistics, local estimates of aggregate inhomogeniety are defined that quantify phenomena that have been qualitatively described in the past. These methods involve modification of the two-dimensional images to prepare them for analysis, as well as simple diagnostic statistics for determining the presence of a wall effect. While the techniques presented herein are developed specifically for cast cylinders, they can be generalized to other cast or cored concrete specimens.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author><author><style face="normal" font="default" size="100%">S.S. Jaiswal</style></author><author><style face="normal" font="default" size="100%">B.E. Ankenman</style></author><author><style face="normal" font="default" size="100%">J.D. Picka</style></author><author><style face="normal" font="default" size="100%">T. Igusa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Impact of the interfacial transition zone on the chloride permeability of concrete</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 12th Engrg. Mechanics Conf</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><pages><style face="normal" font="default" size="100%">1134-1137</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kitamura, Ryuichi</style></author><author><style face="normal" font="default" size="100%">Chen, Cynthia</style></author><author><style face="normal" font="default" size="100%">Pendyala, Ram M.</style></author><author><style face="normal" font="default" size="100%">Narayanan, Ravi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Micro-simulation of daily activity-travel patterns for travel demand forecasting</style></title><secondary-title><style face="normal" font="default" size="100%">Transportation</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">daily activity-travel patterns</style></keyword><keyword><style  face="normal" font="default" size="100%">forecasting</style></keyword><keyword><style  face="normal" font="default" size="100%">micro-simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">synthetic travel patterns</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1023/A%3A1005259324588</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><publisher><style face="normal" font="default" size="100%">Kluwer Academic Publishers</style></publisher><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">25-51</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The development and initial validation results of a micro-simulator for the generation of daily activity-travel patterns are presented in this paper. The simulator assumes a sequential history and time-of-day dependent structure. Its components are developed based on a decomposition of a daily activity-travel pattern into components to which certain aspects of observed activity-travel behavior correspond, thus establishing a link between mathematical models and observational data. Each of the model components is relatively simple and is estimated using commonly adopted estimation methods and existing data sets. A computer code has been developed and daily travel patterns have been generated by Monte Carlo simulation. Study results show that individuals’ daily travel patterns can be synthesized in a practical manner by micro-simulation. Results of validation analyses suggest that properly representing rigidities in daily schedules is important in simulating daily travel patterns.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">S. G. Eick</style></author><author><style face="normal" font="default" size="100%">T.L. Graves</style></author><author><style face="normal" font="default" size="100%">J. S. Marron</style></author><author><style face="normal" font="default" size="100%">H. Siy</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Predicting fault incidence using software change history</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Transportation Software Engineering</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">aging</style></keyword><keyword><style  face="normal" font="default" size="100%">change history</style></keyword><keyword><style  face="normal" font="default" size="100%">degradation</style></keyword><keyword><style  face="normal" font="default" size="100%">management of change</style></keyword><keyword><style  face="normal" font="default" size="100%">software fault tolerance</style></keyword><keyword><style  face="normal" font="default" size="100%">software maintenance</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><number><style face="normal" font="default" size="100%">7</style></number><volume><style face="normal" font="default" size="100%">26</style></volume><pages><style face="normal" font="default" size="100%">653?661</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper is an attempt to understand the processes by which software ages. We define code to be aged or decayed if its structure makes it unnecessarily difficult to understand or change and we measure the extent of decay by counting the number of faults in code in a period of time. Using change management data from a very large, long-lived software system, we explore the extent to which measurements from the change history are successful in predicting the distribution over modules of these incidences of faults. In general, process measures based on the change history are more useful in predicting fault rates than product metrics of the code: For instance, the number of times code has been changed is a better indication of how many faults it will contain than is its length. We also compare the fault rates of code of various ages, finding that if a module is, on the average, a year older than an otherwise similar module, the older module will have roughly a third fewer faults. Our most successful model measures the fault potential of a module as the sum of contributions from all of the times the module has been changed, with large, recent changes receiving the most weight&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">S.S. Jaiswal</style></author><author><style face="normal" font="default" size="100%">T. Igusa</style></author><author><style face="normal" font="default" size="100%">J.D. Picka</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Quantitative description of coarse aggregate volume fraction gradients</style></title><secondary-title><style face="normal" font="default" size="100%">Cement Concrete and Aggregates</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">151-159</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Within any cast cylinder of concrete, the coarse aggregate will tend to be inhomogeneously distributed. This variability may arise as a result of segregation caused by gravity or as a result of the wall effect that is caused by the inability of the aggregate to penetrate the walls of the mold. Using methods from image analysis, stereology, and statistics, local estimates of aggregate inhomogeniety are defined that quantify phenomena that have been qualitatively described in the past. These methods involve modification of the two-dimensional images to prepare them for analysis, as well as simple diagnostic statistics for determining the presence of a wall effect. While the techniques presented herein are developed specifically for cast cylinders, they can be generalized to other cast or cored concrete specimens.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">S.S. Jaiswal</style></author><author><style face="normal" font="default" size="100%">J.D. Picka</style></author><author><style face="normal" font="default" size="100%">T. Igusa</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author><author><style face="normal" font="default" size="100%">B.E. Ankenman</style></author><author><style face="normal" font="default" size="100%">P. Styer</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Statistical studies of the conductivity of concrete using ASTM C1202?94</style></title><secondary-title><style face="normal" font="default" size="100%">Concrete Science and Engineering</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">97-105</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">C.-M. Aldea</style></author><author><style face="normal" font="default" size="100%">S.S. Jaiswal</style></author><author><style face="normal" font="default" size="100%">B.E. Ankenman</style></author><author><style face="normal" font="default" size="100%">J.D. Picka</style></author><author><style face="normal" font="default" size="100%">T. Igusa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Water permeability of cracked concrete</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. 12th Engrg. Mechanics Conf</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><pages><style face="normal" font="default" size="100%">1158?1162</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr.</style></author><author><style face="normal" font="default" size="100%">C.-M. Aldea</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Effect of cracking on water and chloride permeability of concrete</style></title><secondary-title><style face="normal" font="default" size="100%">ACSE Journal of Materials in Civil Engineering</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">181?187</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The goal of this research was to study the relationship between cracking and concrete permeability and to support accounting for permeability and cracking resistance to other factors besides strength, as criteria to be considered in mix design to achieve a durable concrete. The effect of material composition [normal-strength concrete (NSC) and high-strength concrete (HSC) with two different mix designs] and crack width (ranging from 50 to 400 ?m) on water and chloride permeability were examined. Cracks of designed widths were induced in the concrete specimens using a feedback-controlled splitting tensile test. Chloride permeability of the cracked samples was evaluated using a rapid chloride permeability test and the water permeability of cracked concrete was then evaluated by a low-pressure water permeability test. Uncracked HSC was less water permeable than NSC, as expected, but cracking changed the material behavior in terms of permeability. Both NSC and HSC were affected by cracking, and the water permeability of cracked samples increased with increasing crack width. Among the tested materials, only HSC with a very low water-to-cement ratio chloride permeability was sensitive with respect to cracking. Results indicate that the water permeability is significantly more sensitive than the chloride permeability with respect to the crack widths used in this study.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">C.-M. Aldea</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Effect of microcracking on durability of high strength concrete</style></title><secondary-title><style face="normal" font="default" size="100%">Transportation Research Record</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><volume><style face="normal" font="default" size="100%">1668</style></volume><pages><style face="normal" font="default" size="100%">86-90</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The relationship between cracking and chloride and water permeability of high-strength concrete (HSC) was studied. Two different mix designs were used: HSC_1 (w/b = 0.31) and HSC_2 (w/b = 0.25). The effects of crack width and sample thickness on permeability were examined. Cracks of designed widths were induced in the concrete specimens using the feedback-controlled splitting tensile test. Chloride permeability of the cracked samples was evaluated by using a rapid chloride permeability test. The water permeability of cracked concrete was then evaluated by a low-pressure water permeability test. Among the materials tested, only high-strength concrete with a very low water-to-cement ratio conductivity is sensitive with respect to cracking. The water permeability of cracked HSC significantly increases with increasing crack width. Among the parameters considered, crack parameters significantly affect water permeability, and there is little thickness effect. The results indicate that the water permeability is significantly more sensitive than conductivity with respect to the crack width used.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">C.-M. Aldea</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Permeability of cracked concrete</style></title><secondary-title><style face="normal" font="default" size="100%">Materials and Structures</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">370-376</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The goal of the research presented here was to study the relationship between cracking and water permeability. A feedback-controlled test was used to generate width-controlled cracks. Water permeability was evaluated by a low-pressure water permeability test. The factors chosen for the experimental design were material type (paste, mortar, normal and high strength concrete), thickness of the sample and average width of the induced cracks (ranging from 50 to 350 micrometers). The water permeability test results indicated that the relationships between permeability and material type differ for uncracked and cracked material, and that there was little thickness effect. Permeability of uncracked material decreased from paste, mortar, normal strength concrete (NSC) to high strength concrete (HSC). Water permeability of cracked material significantly increased with increasing crack width. For cracks above 100 microns, NSC showed the highest permeability coefficient, where as mortar showed the lowest one.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">C.-M. Aldea</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">P. C. Aïtcin</style></author><author><style face="normal" font="default" size="100%">Y. Delagrave</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Permeability of cracked high strength concrete</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the International Symposium on High Performance and Reactive Powder Concretes</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><pages><style face="normal" font="default" size="100%">211-219</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The goal of the research presented here was to study the relationship between cracking and water permeability. A feedback-controlled test was used to generate width-controlled cracks. Water permeability was evaluated by a low-pressure water permeability test. The factors chosen for the experimental design were material type (paste, mortar, normal and high strength concrete), thickness of the sample and average width of the induced cracks (ranging from 50 to 350 micrometers). The water permeability test results indicated that the relationships between permeability and material type differ for uncracked and cracked material, and that there was little thickness effect. Permeability of uncracked material decreased from paste, mortar, normal strength concrete (NSC) to high strength concrete (HSC). Water permeability of cracked material significantly increased with increasing crack width. For cracks above 100 microns, NSC showed the highest permeability coefficient, where as mortar showed the lowest one.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">P. Thakuriah</style></author><author><style face="normal" font="default" size="100%">A. Sen</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">R. Emmerink</style></author><author><style face="normal" font="default" size="100%">P. Nijkamp</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Probe-based surveillance for travel time information in ITS</style></title></titles><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><publisher><style face="normal" font="default" size="100%">Ashgate Publishing Ltd</style></publisher><pages><style face="normal" font="default" size="100%">393-425</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">17</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">A. Sen</style></author><author><style face="normal" font="default" size="100%">P. Thakuriah</style></author><author><style face="normal" font="default" size="100%">X. Zhu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Variances of link travel time estimates: Implications for optimal routes</style></title><secondary-title><style face="normal" font="default" size="100%">International Transactions in Operational Research</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Advanced Traveler Information System</style></keyword><keyword><style  face="normal" font="default" size="100%">Covariance of travel times</style></keyword><keyword><style  face="normal" font="default" size="100%">Dependence in travel time observations</style></keyword><keyword><style  face="normal" font="default" size="100%">Intelligent Transportation System</style></keyword><keyword><style  face="normal" font="default" size="100%">Probe vehicles</style></keyword><keyword><style  face="normal" font="default" size="100%">Variance of travel time estimates</style></keyword><keyword><style  face="normal" font="default" size="100%">Vehicle simulation model</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1999</style></year><pub-dates><date><style  face="normal" font="default" size="100%">January</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">75-87</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this paper, we explore the consequences of using link travel time estimates with high variance to compute the minimum travel time route between an origin and destination pair. Because of platoon formation or for other reasons, vehicles on a link separated by small headways tend to have similar travel times. In other words, the covariance of link travel times of distinct vehicles which are close together may not be zero. It follows that the variance of the mean of travel times obtained from a sample of n vehicles on a same link over small time intervals is of the form a+b/n where a and b would usually be positive. This result has an important implication for the quality of road network travel time information given by Intelligent Transportation Systems (ITS)?that the variance of the estimate of mean travel time does not go to zero with increasing n. Thus the quality of information disseminated by ITS is not necessarily improved by increasing the market penetration of vehicles monitoring the system with the necessary equipment (termed probe vehicles). Estimates of a and b for a set of links are presented in the paper and consequences for probe-based ITS are explored by means of a simulation of such a system which is operational on an actual network.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Todd L. Graves</style></author><author><style face="normal" font="default" size="100%">Harrold, Mary Jean</style></author><author><style face="normal" font="default" size="100%">Kim, Jung-Min</style></author><author><style face="normal" font="default" size="100%">Adam Porter</style></author><author><style face="normal" font="default" size="100%">Rothermel, Gregg</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An Empirical Study of Regression Test Selection Techniques</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 20th International Conference on Software Engineering</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">ICSE ’98</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dl.acm.org/citation.cfm?id=302163.302182</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE Computer Society</style></publisher><pub-location><style face="normal" font="default" size="100%">Washington, DC, USA</style></pub-location><pages><style face="normal" font="default" size="100%">188–197</style></pages><isbn><style face="normal" font="default" size="100%">0-8186-8368-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alan Karr</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">C. E. Minder</style></author><author><style face="normal" font="default" size="100%">F. Friedl</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Good Statistical Practice</style></title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><publisher><style face="normal" font="default" size="100%">Austrian Statistical Society</style></publisher><pages><style face="normal" font="default" size="100%">175?179</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">Modeling software changes</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">G. Eick</style></author><author><style face="normal" font="default" size="100%">A. Mockus</style></author><author><style face="normal" font="default" size="100%">T.L. Graves</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">W. Badilla</style></author><author><style face="normal" font="default" size="100%">F. Faulbaum</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">SoftStat ?97: Advances in Statistical Software 6</style></title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><publisher><style face="normal" font="default" size="100%">Lucius &amp; Lucius</style></publisher><pages><style face="normal" font="default" size="100%">3-10</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">Web-based text visualization</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kitamura, Ryuichi</style></author><author><style face="normal" font="default" size="100%">Chen, Cynthia</style></author><author><style face="normal" font="default" size="100%">Narayanan, Ravi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Traveler Destination Choice Behavior: Effects of Time of Day, Activity Duration and Home Location</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Choice models</style></keyword><keyword><style  face="normal" font="default" size="100%">Hypothesis testing</style></keyword><keyword><style  face="normal" font="default" size="100%">Logits</style></keyword><keyword><style  face="normal" font="default" size="100%">Multinomial logits</style></keyword><keyword><style  face="normal" font="default" size="100%">Origin and destination</style></keyword><keyword><style  face="normal" font="default" size="100%">Periods of the day</style></keyword><keyword><style  face="normal" font="default" size="100%">Residential location</style></keyword><keyword><style  face="normal" font="default" size="100%">Time duration</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><pages><style face="normal" font="default" size="100%">76-81</style></pages><isbn><style face="normal" font="default" size="100%">0309065178</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Multinomial logit destination choice models are developed and the following hypotheses are examined: (a) time of day affects destination choice behavior, (b) the duration of stay at the destination affects destination choice, and (c) home location affects non-home-based destination choice. The statistical results offer strong evidence in support of the hypotheses.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">G. Eick</style></author><author><style face="normal" font="default" size="100%">A. Mockus</style></author><author><style face="normal" font="default" size="100%">T.L. Graves</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Web laboratory for software data analysis</style></title><secondary-title><style face="normal" font="default" size="100%">World Wide Web</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">55-60</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We describe two prototypical elements of a World Wide Web?based system for visualization and analysis of data produced in the software development process. Our system incorporates interactive applets and visualization techniques into Web pages. A particularly powerful example of such an applet, SeeSoftTM, can display thousands of lines of text on a single screen, allowing detection of patterns not discernible directly from the text. In our system, Live Documents replace static statistical tables in ordinary documents by dynamic Web?based documents, in effect allowing the ?reader? to customize the document as it is read. Use of the Web provides several advantages. The tools access data from a very large central data base, instead of requiring that it be downloaded; this ensures that readers are always working with the most up?to?date version of the data, and relieves readers of the responsibility of preparing data for their use. The tools encourage collaborative research, as one researcher’s observations can easily be replicated and studied in greater detail by other team members. We have found this particularly useful while studying software data as part of a team that includes researchers in computer science, software engineering, and statistics, as well as development managers. Live documents will also help the Web revolutionize scientific publication, as papers published on the Web can contain Java applets that permit readers to confirm the conclusions reached by the authors’ statistical analyses.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. Sen</style></author><author><style face="normal" font="default" size="100%">P. Thakuriah</style></author><author><style face="normal" font="default" size="100%">X. Zhu</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Frequency of probe vehicle reports and variances of link travel time estimates</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Transportation Engineering, ASCE</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1997</style></year></dates><volume><style face="normal" font="default" size="100%">123</style></volume><pages><style face="normal" font="default" size="100%">290?297</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;An important design issue relating to probe-based Advanced Traveler Information Systems (ATISs) and Advanced Traffic Management Systems is the sample size of probes (or the number of link traversals by probe vehicles) per unit time used in order to obtain reliable network information in terms of link travel time estimates. The variance of the mean of travel times obtained from n probes for the same link over a fixed time period may be shown to be of the form a+b/n where a and b are link-specific parameters. Using probe travel time data from a set of signalized arterials, it is shown that a is positive for well-traveled signalized links. This implies that the variance does not go to zero with increasing n. Consequences of this fact for probe-based systems are explored. While the results presented are for a specific set of links, we argue that because of the nature of the underlying travel time process, the broad conclusions would hold for most well-traveled links with signal control.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">S. Jaiswal</style></author><author><style face="normal" font="default" size="100%">T. Igusa</style></author><author><style face="normal" font="default" size="100%">T. Styer</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Influence of microstructure and fracture on the transport properties in cement-based materials</style></title><secondary-title><style face="normal" font="default" size="100%">Brittle Matrix Composites - International Symposium</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1997</style></year></dates><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">199-220</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">K. Wang</style></author><author><style face="normal" font="default" size="100%">D.C. Jansen</style></author><author><style face="normal" font="default" size="100%">S. P. Shah</style></author><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Permeability study of cracked concrete</style></title><secondary-title><style face="normal" font="default" size="100%">Cement Concrete Res.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1997</style></year></dates><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">381-393</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Cracks in concrete generally interconnect flow paths and increase concrete permeability. The increase in concrete permeability due to the progression of cracks allows more water or aggressive chemical ions to penetrate into the concrete, facilitating deterioration. The present work studies the relationship between crack characteristics and concrete permeability. In this study, feedback controlled splitting tests are introduced to generate crack width-controlled concrete specimens. Sequential crack patterns with different crack widths are viewed under a microscope. The permeability of cracked concrete is evaluated by water permeability tests. The preliminary results indicate that crack openings generally accelerate water flow rate in concrete. When a specimen is loaded to have a crack opening displacement smaller than 50 microns prior to unloading, the crack opening has little effect on concrete permeability. When the crack opening displacement increases from 50 microns to about 200 microns, concrete permeability increases rapidly. After the crack opening displacement reaches 200 microns, the rate of water permeability increases steadily. The present research may provide insight into developing design criteria for a durable concrete and in predicting service life of a concrete structure.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nobile, Agostino</style></author><author><style face="normal" font="default" size="100%">Bhat, Chandra R.</style></author><author><style face="normal" font="default" size="100%">Pas, Eric I.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Gatsonis, Constantine</style></author><author><style face="normal" font="default" size="100%">Hodges, JamesS.</style></author><author><style face="normal" font="default" size="100%">Kass, RobertE.</style></author><author><style face="normal" font="default" size="100%">McCulloch, Robert</style></author><author><style face="normal" font="default" size="100%">Rossi, Peter</style></author><author><style face="normal" font="default" size="100%">Singpurwalla, NozerD.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">A Random-Effects Multinomial Probit Model of Car Ownership Choice</style></title><secondary-title><style face="normal" font="default" size="100%">Case Studies in Bayesian Statistics</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Statistics</style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">car ownership</style></keyword><keyword><style  face="normal" font="default" size="100%">longitudinal data</style></keyword><keyword><style  face="normal" font="default" size="100%">Multinomial probit model</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1997</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-1-4612-2290-3_13</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer New York</style></publisher><volume><style face="normal" font="default" size="100%">121</style></volume><pages><style face="normal" font="default" size="100%">419-434</style></pages><isbn><style face="normal" font="default" size="100%">978-0-387-94990-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The number of cars in a household has an important effect on its travel behavior (e.g., choice of number of trips, mode to work and non-work destinations), hence car ownership modeling is an essential component of any travel demand forecasting effort. In this paper we report on a random effects multinomial probit model of car ownership level, estimated using longitudinal data collected in the Netherlands. A Bayesian approach is taken and the model is estimated by means of a modification of the Gibbs sampling with data augmentation algorithm considered by McCulloch and Rossi (1994). The modification consists in performing, after each Gibbs sampling cycle, a Metropolis step along a direction of constant likelihood. An examination of the simulation output illustrates the improved performance of the resulting sampler.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author><author><style face="normal" font="default" size="100%">A. A. Porter</style></author><author><style face="normal" font="default" size="100%">L. G. Votta</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An empirical exploration of code evolution</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the InternationalWorkshop on Empirical Studies of Software Maintenance</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1996</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">de Leeuw, Jan</style></author><author><style face="normal" font="default" size="100%">Kreft, Ita G.G.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Questioning Multilevel Models</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Educational and Behavioral Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1995</style></year></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">171-189</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In this article, practical problems with multilevel techniques are discussed. These problems, brought to our attention by the National Center for Education Statistics (NCES), have to do with terminology, computer programs employing different algorithms, and interpretations of the coefficients in one or two steps. We discuss the usefulness of the hierarchical linear model (HM) in the most common situation in education-that of a large number of relatively small groups. We also point to situations where the more complicated HMs can be replaced with simpler models, with statistical properties that are easier to study. We conclude that more studies need to be done to establish the claimed superiority of restricted versus unrestricted maximum likelihood, to study the effects of shrinkage on the estimators, and to explore the merits of simpler methods such as weighted least squares. Finally, distinctions must be made between choice of model, choice of technique, choice of algorithm, and choice of computer program. While HMs are an elegant conceptualization, they are not always necessary. Traditional techniques perform as well, or better, if there are large groups and small intraclass correlations, and if the researcher is interested only in the fixed-level regression coefficients.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. F. Karr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Statistics and Materials Science: Report of a Workshop</style></title></titles><dates><year><style  face="normal" font="default" size="100%">1994</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><publisher><style face="normal" font="default" size="100%">National Institute of Statistical Sciences</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>