Extensions of the Partial Credit Model
Copyright policy )Extensions of the Partial Credit Model
The partial credit model, developed by Masters (1982), is a unidimensional latent trait model for responses scored in two or more ordered categories. In the present paper some extensions of the model are presented. First, a marginal maximum likelihood estimation procedure is developed which allows for incomplete data and linear restrictions on both the item and the population parameters. Secondly, two statistical tests for evaluating model fit are presented: the former test has power against violation of the assumption about the ability distribution, the latter test offers the possibility of identifying specific items that do not fit the model.
latent trait model, incomplete data, EM-algorithm, partial credit model, ability distribution, item response theory, evaluating model fit, marginal maximum likelihood estimation procedure, model test, linear restrictions, partial credit, ordered categories, Rasch model, Applications of statistics to psychology
latent trait model, incomplete data, EM-algorithm, partial credit model, ability distribution, item response theory, evaluating model fit, marginal maximum likelihood estimation procedure, model test, linear restrictions, partial credit, ordered categories, Rasch model, Applications of statistics to psychology
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