Handbook of Item Response Theory : Volume 2: Statistical Tools (Paperback)

Basic ToolsLogit, Probit, and Other Response FunctionsJames H. AlbertDiscrete Distributions Jodi M. Casabianca and Brian W. JunkerMultivariate Normal Distribution Jodi M. Casabianca and Brian W. JunkerExponential Family Distributions Relevant to IRT Shelby J. HabermanLoglinear Models for Observed-Score Distributions Tim MosesDistributions of Sums of Nonidentical Random Variables Wim J. van der LindenInformation Theory and Its Application to Testing Hua-Hua Chang, Chun Wang, and Zhiliang Ying Modeling IssuesIdentification of Item Response Theory Models Ernesto San MartinModels with Nuisance and Incidental Parameters Shelby J. HabermanMissing Responses in Item Response Modeling Robert J. Mislevy Parameter EstimationMaximum-Likelihood Estimation Cees A. W. GlasExpectation Maximization Algorithm and Extensions Murray AitkinBayesian Estimation Matthew S. Johnson and Sandip SinharayVariational Approximation Methods Frank Rijmen, Minjeong Jeon, and Sophia Rabe-HeskethMarkov ChainMonte Carlo for Item Response Models Brian W. Junker, Richard J. Patz, and Nathan M. VanHoudnosStatistical Optimal Design Theory Heinz Holling and Rainer Schwabe Model Fit and ComparisonFrequentist Model-Fit Tests Cees A. W. GlasInformation Criteria Allan S. Cohen and Sun-Joo ChoBayesian Model Fit and Model Comparison Sandip SinharayModel Fit with Residual Analyses Craig S. Wells and Ronald K. Hambleton