<?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%">Erciulescu A.L.</style></author><author><style face="normal" font="default" size="100%">Berg E.</style></author><author><style face="normal" font="default" size="100%">Cecere W.</style></author><author><style face="normal" font="default" size="100%">Ghosh M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Bivariate Hierarchical Bayesian Model for Estimating Cropland Cash Rental Rates at the County Level.</style></title><secondary-title><style face="normal" font="default" size="100%">Survey Methodology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">In Press</style></year></dates></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%">Bellow, Michael E.</style></author><author><style face="normal" font="default" size="100%">Cruze, Nathan</style></author><author><style face="normal" font="default" size="100%">Erciulescu, Andreea L.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Developments in Model-Based County Level Estimation of Agricultural Cash Rental Rates</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%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.niss.org/sites/default/files/2017%20-%20Developments%20in%20Model-Based%20County-Level%20Estimation%20of%20Ag%20Cash%20Rental%20Rates.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%">2773 - 2790</style></section></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%">Erciulescu, Andreea L.</style></author><author><style face="normal" font="default" size="100%">Cruze, Nathan B.</style></author><author><style face="normal" font="default" size="100%">Nandram, Balgobin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Small Area Estimates for End-of-Season Agricultural Quantities</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%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.niss.org/sites/default/files/2017%20-%20Small%20Area%20Estimates%20for%20End-Of-Season%20Agricultural%20Quantities.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%">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>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>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>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>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">A. Dobra</style></author><author><style face="normal" font="default" size="100%">E. A. Erosheva</style></author><author><style face="normal" font="default" size="100%">S. E. Fienberg</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Disclosure limitation methods based on bounds for large contingency tables with application to disability data</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of Conference on New Frontiers of Statistical Data Mining</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%">CRC Press</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><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%">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>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>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>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>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>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%">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%">Dennis D. Cox</style></author><author><style face="normal" font="default" size="100%">Lawrence H. Cox</style></author><author><style face="normal" font="default" size="100%">ENSOR, KATHERINE B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spatial sampling and the environment: some issues and directions</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental and Ecological Statistics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">environmental monitoring</style></keyword><keyword><style  face="normal" font="default" size="100%">experimental design</style></keyword><keyword><style  face="normal" font="default" size="100%">kriging</style></keyword><keyword><style  face="normal" font="default" size="100%">multiphase sampling</style></keyword><keyword><style  face="normal" font="default" size="100%">spatial statistics</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/10.1023/A%3A1018578513217</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><publisher><style face="normal" font="default" size="100%">Kluwer Academic Publishers</style></publisher><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">219-233</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%">Elliott, M. R.</style></author><author><style face="normal" font="default" size="100%">Raghunathan, T. E.</style></author><author><style face="normal" font="default" size="100%">Schenker, N.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Combining Estimates from Multiple Surveys</style></title><secondary-title><style face="normal" font="default" size="100%">Wiley StatsRef: Statistics Reference Online</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">dual frame</style></keyword><keyword><style  face="normal" font="default" size="100%">imputation</style></keyword><keyword><style  face="normal" font="default" size="100%">missing data</style></keyword><keyword><style  face="normal" font="default" size="100%">non-probability samples</style></keyword><keyword><style  face="normal" font="default" size="100%">small-area estimation</style></keyword><keyword><style  face="normal" font="default" size="100%">Weighting</style></keyword></keywords><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.niss.org/sites/default/files/Elliott%2C%20Raghunathan%2C%20%26%20Schenker%20for%20Wiley%20StatsRef.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Combining estimates from multiple surveys can be very useful, especially when the question of interest cannot be&amp;nbsp;addressed well by a single, existing survey. In this paper, we provide a brief review of methodology for combining&amp;nbsp;estimates, with a focus on dual frame, weighting-based, joint-modeling, missing-data, and small-area methods.&amp;nbsp;Many such methods are useful in situations outside the realm of combining estimates from surveys, such as&amp;nbsp;combining information from surveys with administrative data and combining probability-sample data with&amp;nbsp;non-probability sample, or “big” data. We also provide examples of comparability issues that must be kept in mind&amp;nbsp;when information from different sources is being combined.&lt;/p&gt;
</style></abstract><custom1><style face="normal" font="default" size="100%">&lt;p&gt;https://www.niss.org/sites/default/files/Elliott%2C%20Raghunathan%2C%20%26%20Schenker%20for%20Wiley%20StatsRef.pdf&lt;/p&gt;
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