Using SAS PROC MCMC for Item Response Theory Models

Author:

Ames Allison J.1,Samonte Kelli1

Affiliation:

1. University of North Carolina at Greensboro, Greensboro, NC, USA

Abstract

Interest in using Bayesian methods for estimating item response theory models has grown at a remarkable rate in recent years. This attentiveness to Bayesian estimation has also inspired a growth in available software such as WinBUGS, R packages, BMIRT, MPLUS, and SAS PROC MCMC. This article intends to provide an accessible overview of Bayesian methods in the context of item response theory to serve as a useful guide for practitioners in estimating and interpreting item response theory (IRT) models. Included is a description of the estimation procedure used by SAS PROC MCMC. Syntax is provided for estimation of both dichotomous and polytomous IRT models, as well as a discussion on how to extend the syntax to accommodate more complex IRT models.

Publisher

SAGE Publications

Subject

Applied Mathematics,Applied Psychology,Developmental and Educational Psychology,Education

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