Latent trait models and ability parameter estimation

Abstract

In recent years several authors have viewed latent trait models for binary data as special models for contingency tables. This connection to contingency table analysis is used as the basis for a survey of various latent trait models. This article discusses estimation of item parameters by conditional, direct, and marginal maximum likelihood methods, and estimation of individual latent parameters as opposed to an estimation of the parameters of a latent population density. Various methods for testing the goodness of fit of the model are also described. Several of the estimators and tests are applied to a data set concerning consumer complaint behavior.