v 1.1
d openirt. Bayesian and Maximum Likelihood Estimation of Item Response Theory (IRT) models.
d Tristan Zajonc (tzajonc@fas.harvard.edu).
d
d OpenIRT estimates 2PL and 3PL Item Response Theory (IRT) models for dichotomous data.
d It includes Bayesian MCMC estimation of item parameters and abilities, and maximum
d likelihood ability estimates.  The Bayesian methods includes both expected 
d posterior (EAP) and plausible values (PV) ability and item parameter estimates.
d
d OpenIRT is designed to be flexible. It allows any combination of items, abilities, 
d and responses to be missing.  For instance, fixed anchor items can be used to place
d children and items on a known scale; missing responses can be used to link multiple
d overlapping test forms; and known abilities can be used to calibrate new items 
d and ability parameters.  
d
d OpenIRT relies on compiled code that works on Windows, Mac, and Linux.

f openirt.ado
f openirt.sthlp
G WIN	OpenIRT.exe	openirt.exe
G WIN64A	OpenIRT.exe	openirt.exe
G WIN64I	OpenIRT.exe	openirt.exe
G MAC	openirt_osx	openirt.exe
G MACINTEL	openirt_osx	openirt.exe
G MACINTEL64	openirt_osx	openirt.exe
G LINUX openirt_linux openirt.exe
F openirt.ini
F naep_children.dta
F naep_items.dta
F timss_children.dta
F timss_items.dta
F openirt_examples.do