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

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