OpenIRT v. 1.0 - Bayesian and Maximum Likelihood Estimation of IRT Models.

AUTHOR:

Tristan Zajonc

John F. Kennedy School of Government

Harvard University, Cambridge, MA 02138.

Email: tzajonc@fas.harvard.edu

Web: http://people.fas.harvard.edu/~tzajonc

DESCRIPTION:

OpenIRT estimates 2PL and 3PL Item Response Theory (IRT) models for

dichotomous data. It includes Bayesian MCMC estimation of item parameters

and abilities, and maximum likelihood ability estimates.  The Bayesian

methods include both expected posterior (EAP) and plausible values (PV)

ability and item parameter estimates.

OpenIRT is designed to be flexible. It allows any combination of items,

abilities, and responses to be missing.  For instance, fixed anchor

items can be used to place children and items on a known scale; missing

responses can be used to link multiple overlapping test forms; and known

abilities can be used to calibrate new items and ability parameters.

INSTALLATION:

In Stata:

. net install http://people.fas.harvard.edu/~tzajonc/stata/openirt

. help openirt