|Authors:||Matthew S. Johnson|
|Title:||Marginal Maximum Likelihood Estimation of Item Response Models in R|
|Abstract:||Item response theory (IRT) models are a class of statistical models used by researchers to describe the response behaviors of individuals to a set of categorically scored items. The most common IRT models can be classified as generalized linear fixed- and/or mixed-effect models. Although IRT models appear most often in the psychological testing literature, researchers in other fields have successfully utilized IRT-like models in a wide variety of applications. This paper discusses the three major methods of estimation in IRT and develops R functions utilizing the built-in capabilities of the R environment to find the marginal maximum likelihood estimates of the generalized partial credit model. The currently available R packages ltm is also discussed.|
Page views:: 20643. Submitted: 2006-10-01. Published: 2007-02-22.
Marginal Maximum Likelihood Estimation of Item Response Models in R
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