Multidimensional Rasch Models for Partial-Credit Scoring

Abstract

Rasch models for partial-credit scoring are discussed and a multidimensional version of the model is formu lated. A model may be specified in which consecutive item responses depend on an underlying latent trait. In the multidimensional partial-credit model, different re sponses may be explained by different latent traits. Data from van Kuyk's (1988) size concept test and the Raven Progressive Matrices test were analyzed. Maximum likelihood estimation and goodness-of-fit testing are dis cussed and applied to these datasets. Goodness-of-fit statistics show that for both tests, multidimensional par tial-credit models were more appropriate than the unidi mensional partial-credit model.