●Contents for ModelsContents for ApplicationsPrefaceContributorsSection Ⅰ Basic Tools 1.Logit, Probit, and Other Response Functions James H. Albert 2.Discrete Distributions Jodi M. Casabianca and Brian W. Junker 3. ltivariate Normal Distribution Jodi M. Casabianca and Brian W. Junker 4.Exponential Family Distributions Relevant to IRT Shelby J. Haberman 5.Loglinear Models for Observed-Score Distributions Tim Moses 6.Distributions of Sums of Nonidentical Random Variables . Wire J. van der Linden 7.Information Theory and Its Application to Testing Hua-Hua Chang, Chun Wang, and Zhiliang YingSection Ⅱ Modeling Issues 8.Identification of Item Response Theory Models Ernesto San Martin 9.Models with Nuisance and Incidental Parameters Shelby J. Haberman 10. Missing Responses in Item Response Modeling Robert J. MislevySection Ⅲ Parameter Estimation 11. Maximum-Likelihood Estimation Cees A. W. Glas 12. Expectation Maximization Algorithm and Extensions rray Aitkin 13. Bayesian Estimation Matthew S. Johnson and Sandip Sinharay 14. Variational Approximation Methods Frank Rijmen, Minjeong Jeon, and Sophia Rabe-Hesketh 15. Markov Chain Monte Carlo for Item Response Models... Brian W. Junker, Richard J. Patz, and Nathan M. VanHoudnos 16. Statistical Optimal Design Theory Heinz Holling and Rainer SchwabeSection Ⅳ Model Fit and Comparison 17. Frequentist Model-Fit Tests Cees A. W. Glas 18. Information Criteria Allan S. Cohen and Sun-Joo Cho 19. Bayesian Model Fit and Model Comparison Sandip Sinharay 20. Model Fit with Residual Analyses Craig S. Wells and Ronald K. HambletonIndex編輯手記

本書是一部大型的英文版的應用統計學著作，是社會與行為科學中的統計學繫列中的一本。本書借鋻了該領域國際知名專家的工作，並且提供了在項目反應理論中用到的經典和現代統計工具，雖然項目反應理論十分依賴於用統計工具來處理其模型和應用，但是繫統的介紹且著重於與項目反應理論相關的統計學文獻幾乎很難被找到，本書就填補了這一空白.本書包含了常見的統計分布，同時也包含了具有目的和干擾參數的模型問題，信息標準的應用，缺失信息的處理方法，以及模型識別問題，強調了參數估計和模型擬合與比較的近期發展，例如貝葉斯方法，尤其是馬爾可夫鏈蒙特·卡洛(MCMC)方法。