This is a library with functions to estimate the items and abilities from the responses of subjects to a questionnaire.
The supported IRT (Item Response Theory) model are the Rasch model, the 2PLM (two parameter logistic model) and the 3PLM (three parameter logistic model). The multivariate logistic model and non parametric methods are also supported.
The estimations methods available are the MMLE (Marginal Maximum Likelihood Estimator) and the BME (Bayes Modal Estimator) for the parametric estimation of items, the PMMLE (Penalized MMLE) and kernel smoothing for the non parametric estimation of items, and the ML (Maximum Likelihood) and the EAP (Expected A Posteriori) estimators for the abilities.
Two command line programs called "irt" and "mirt" are also provided.
See http://libirt.sf.net .
Baker, F.B. & Kim, S.-H. (2004). Item response theory: parameter estimation techniques. Second Edition. Dekker, New York.
Ramsay, J.O. (1991). Kernel smoothing approaches to nonparametric item characteristic curve estimation. Biometrika, 56, 611-630.
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