From the Book - 2nd ed., rev. and expanded.
Preface to the second edition
Preface to the first edition
1. The item characteristic curve : dichotomous response
2. Estimating the parameters of an item characteristic curve
3. Maximum likelihood estimation of examinee ability
4. Procedures for estimating both ability and item parameters
6. Parameter estimation via MMLE and an EM algorithm
7. Bayesian parameter estimation procedures
8. The graded item response
9. Nominally scored items
10. Parameter estimation for multiple group data
11. Estimation of item parameters of mixed models
12. Parameter estimation via Gibbs sampler
A. Implementation of maximum likelihood estimation of item parameters
B. Implementation of maximum likelihood estimation of examinee's ability
C. Implementation of JMLE procedure for the Rasch model
D. Implementation of item parameter estimation via MMLE-EM
E. Implementing the Bayesian approach
F. Implementation of parameter estimation under the graded response model
G. Implementation of MLE under nominal response scoring H. Implementation of MMLE/EM for the Rasch model
I. Implementation of multiple groups estimation
J. Implementation of estimation for mixed models
K. Implementation of Gibbs sampler
