<?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%">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%">W. Cui</style></author><author><style face="normal" font="default" size="100%">Nell Sedransk</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Psychometric Invariance of Online Reading Comprehension Assessment across Measurement Conditions</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%">Mo, Y.</style></author><author><style face="normal" font="default" size="100%">Troia, G. A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Predicting Students’ Writing Performance on the NAEP from Student- and State-level Variables</style></title><secondary-title><style face="normal" font="default" size="100%">Reading &amp; Writing: An Interdisciplinary Journal</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%">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><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>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael Last</style></author><author><style face="normal" font="default" size="100%">Gheorghe Luta</style></author><author><style face="normal" font="default" size="100%">Alex Orso</style></author><author><style face="normal" font="default" size="100%">Adam Porter</style></author><author><style face="normal" font="default" size="100%">Stan Young</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pooled ANOVA</style></title><secondary-title><style face="normal" font="default" size="100%">Computational Statistics &amp; Data Analysis</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%">52</style></volume><pages><style face="normal" font="default" size="100%">5215</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%">Feng J.</style></author><author><style face="normal" font="default" size="100%">Sanil A</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%">PharmID: Pharmacophore identification using Gibbs sampling</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Chemical Information and Modeling</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%">46</style></volume><pages><style face="normal" font="default" size="100%">1352-1359</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 binding of a small molecule to a protein is inherently a 3D matching problem. As crystal structures are not available for most drug targets, there is a need to be able to infer from bioassay data the key binding features of small molecules and their disposition in space, the pharmacophore. Fingerprints of 3D features and a modification of Gibbs sampling to align a set of known flexible ligands, where all compounds are active, are used to discern possible pharmacophores. A clique detection method is used to map the features back onto the binding conformations. The complete algorithm is described in detail, and it is shown that the method can find common superimposition for several test data sets. The method reproduces answers very close to the crystal structure and literature pharmacophores in the examples presented. The basic algorithm is relatively fast and can easily deal with up to 100 compounds and tens of thousands of conformations. The algorithm is also able to handle multiple binding mode problems, which means it can superimpose molecules within the same data set according to two different sets of binding features. We demonstrate the successful use of this algorithm for multiple binding modes for a set of D2 and D4 ligands.&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%">Liu, J.</style></author><author><style face="normal" font="default" size="100%">J. Feng</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%">PowerMV: A Software Environment for Molecular Viewing, Descriptor Generation, Data Analysis and Hit Evaluation</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Chemical Information and Modeling</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%">45</style></volume><pages><style face="normal" font="default" size="100%">515-522</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Ideally, a team of biologists, medicinal chemists and information specialists will evaluate the hits from high throughput screening. In practice, it often falls to nonmedicinal chemists to make the initial evaluation of HTS hits. Chemical genetics and high content screening both rely on screening in cells or animals where the biological target may not be known. There is a need to place active compounds into a context to suggest potential biological mechanisms. Our idea is to build an operating environment to help the biologist make the initial evaluation of HTS data. To this end the operating environment provides viewing of compound structure files, computation of basic biologically relevant chemical properties and searching against biologically annotated chemical structure databases. The benefit is to help the nonmedicinal chemist, biologist and statistician put compounds into a potentially informative biological context. Although there are several similar public and private programs used in the pharmaceutical industry to help evaluate hits, these programs are often built for computational chemists. Our program is designed for use by biologists and statisticians.&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%">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>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%">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>32</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">R. Paulo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Problems on the Bayesian-Frequentist Interface</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><publisher><style face="normal" font="default" size="100%">Duke University</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">masters</style></work-type></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%">Z. He</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Propriety of posteriors with improper priors in hierarchical linear mixed models</style></title><secondary-title><style face="normal" font="default" size="100%">Statistica Sinica</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%">2</style></volume><pages><style face="normal" font="default" size="100%">77-95</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><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%">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>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%">Speckman, Paul</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Posterior distribution of hierarchical models using CAR(1) distributions</style></title><secondary-title><style face="normal" font="default" size="100%">Biometrika</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Gibbs sampling</style></keyword><keyword><style  face="normal" font="default" size="100%">Linear mixed model</style></keyword><keyword><style  face="normal" font="default" size="100%">Multivariate normal</style></keyword><keyword><style  face="normal" font="default" size="100%">Partially informative normal distribution</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1999</style></year></dates><volume><style face="normal" font="default" size="100%">86</style></volume><pages><style face="normal" font="default" size="100%">341-350</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 examine properties of the conditional autoregressive model, or CAR(1) model, which is commonly used to represent regional effects in Bayesian analyses of mortality rates. We consider a Bayesian hierarchical linear mixed model where the fixed effects have a vague prior such as a constant prior and the random effect follows a class of CAR(1) models including those whose joint prior distribution of the regional effects is improper. We give sufficient conditions for the existence of the posterior distribution of the fixed and random effects and variance components. We then prove the necessity of the conditions and give a one-way analysis of variance example where the posterior may or may not exist. Finally, we extend the result to the generalised linear mixed model, which includes as a special case the Poisson log-linear model commonly used in disease&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%">Williams, Valerie</style></author><author><style face="normal" font="default" size="100%">Billeaud, Kathleen</style></author><author><style face="normal" font="default" size="100%">Davis, Lori A.</style></author><author><style face="normal" font="default" size="100%">Thissen, David</style></author><author><style face="normal" font="default" size="100%">Sanford, Eleanor E.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Projecting to the NAEP Scale: Results from the North Carolina End-of-Grade Testing Program</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Educational Measurement</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%">35</style></volume><pages><style face="normal" font="default" size="100%">277-296</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Data from the North Carolina End-of-Grade test of eighth-grade mathematics are used to estimate the achievement results on the scale of the National Assessment of Educational Progress (NAEP) Trial State Assessment. Linear regression models are used to develop projection equations to predict state NAEP results in the future, and the results of such predictions are compared with those obtained in the 1996 administration of NAEP. Standard errors of the parameter estimates are obtained using a bootstrap resampling technique.&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%">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>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gao, Feng</style></author><author><style face="normal" font="default" size="100%">Jerome Sacks</style></author><author><style face="normal" font="default" size="100%">Welch, William</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Predicting ozone levels and trends with semiparametric modeling</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Agricultural, Biological, and Environmental Statistics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1996</style></year></dates><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">404-425</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">404</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%">Smith, R.L.</style></author><author><style face="normal" font="default" size="100%">Shively, Thomas S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Point process approach to modeling trends in tropospheric ozone based on exceedances of a high threshold</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Environment</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%">29</style></volume><pages><style face="normal" font="default" size="100%">3489–3499</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">3489</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%">Gough, William A.</style></author><author><style face="normal" font="default" size="100%">Welch, William J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Parameter space exploration of an ocean general circulation model using an isopycnal mixing parameterization</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Marine Research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1994</style></year></dates><volume><style face="normal" font="default" size="100%">52</style></volume><pages><style face="normal" font="default" size="100%">773-796</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this study we have employed statistical methods to efficiently design experiments and analyze output of an ocean general circulation model that uses an isopycnal mixing parameterization. Full ranges of seven inputs are explored using 51 numerical experiments. Fifteen of the cases fail to reach satisfactory equilibria. These are attributable to numerical limitations specific to the isopycnal model. Statistical approximating functions are evaluated using the remaining cases to determine the dependency of each of the six scalar outputs on the inputs. With the exception of one output, the approximating functions perform well. Known sensitivities, particularly the importance of diapycnal (vertical) eddy diffusivity and wind stress, are reproduced. The sensitivities of the model to two numerical constraints specific to the isopycnal parameterization, maximum allowable isopycnal slope and horizontal background eddy diffusivity, are explored. Isopycnal modelling issues, convection reduction and the Veronis effect, are examined and found to depend crucially on the isopycnal modelling constraints.</style></abstract></record></records></xml>