Abstract: Basic Tools Logit, Probit, and Other Response Functions James H. Albert Discrete Distributions Jodi M. Casabianca and Brian W. Junker Multivariate Normal Distribution Jodi M. Casabianca and Brian W. Junker Exponential Family Distributions Relevant to IRT Shelby J. Haberman Loglinear Models for Observed-Score Distributions Tim Moses Distributions of Sums of Nonidentical Random Variables Wim J. van der Linden Information Theory and Its Application to Testing Hua-Hua Chang, Chun Wang, and Zhiliang Ying Modeling Issues Identification of Item Response Theory Models Ernesto San Martin Models with Nuisance and Incidental Parameters Shelby J. Haberman Missing Responses in Item Response Modeling Robert J. Mislevy Parameter Estimation Maximum-Likelihood Estimation Cees A. W. Glas Expectation Maximization Algorithm and Extensions Murray Aitkin Bayesian Estimation Matthew S. Johnson and Sandip Sinharay Variational Approximation Methods Frank Rijmen, Minjeong Jeon, and Sophia Rabe-Hesketh Markov ChainMonte Carlo for Item Response Models Brian W. Junker, Richard J. Patz, and Nathan M. VanHoudnos Statistical Optimal Design Theory Heinz Holling and Rainer Schwabe Model Fit and Comparison Frequentist Model-Fit Tests Cees A. W. Glas Information Criteria Allan S. Cohen and Sun-Joo Cho Bayesian Model Fit and Model Comparison Sandip Sinharay Model Fit with Residual Analyses Craig S. Wells and Ronald K. Hambleton
Publication Year: 2017
Publication Date: 2017-03-31
Language: en
Type: book
Indexed In: ['crossref']
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Cited By Count: 93
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