EXCEL下IRT插件
http://sourceforge.net/projects/libirt/files/eirt
http://libirt.sourceforge.net/

MODELS
1PLM - One parameter logistic model. The threshold (difficulty or location parameter) of each item is estimated while the slope (discrimination or scale parameter) of each item can be fixed.
2PLM - Two parameters logistic model. Both the threshold and slope of each item are estimated.
3PLM - Three parameters logistic model. The threshold, slope and asymptote (guessing parameter) are estimated.
Bock's nominal response model - The threshold and slope of each option are estimated.
Samejima's graded response model - The modal threshold of each option and the slope of each item are estimated.
Nonparametric - In addition to the parametric models, libirt can estimate the response functions by smoothing (see the methods section).
METHODS
The parametric estimators are:
MMLE - Marginal Maximum Likelihood Estimator.
BME - Bayes Modal Estimator.
The nonparametric estimators are:
Kernel smoothing - The Nadaraya-Watson regression used in TestGraf.
PMMLE - Penalized Marginal Maximum Likelihood Estimator.
The abilities estimators are:
EAP - Expected A Posteriori.
WMLE - Warm's Weighted Maximum Likelihood Estimator.