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A Generalized Rasch Model for Manifest Predictors

Published online by Cambridge University Press:  01 January 2025

Aeilko H. Zwinderman
Aeilko H. Zwinderman*
Affiliation:
Department of Medical Statistics, University of Leiden
*
Requests for reprints should be sent to Aeilko H. Zwinderman, Department of Medical Statistics, University of Leiden, P.O. Box 9512, 2300 RA Leiden, THE NETHERLANDS.
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Abstract

A logistic regression model is suggested for estimating the relation between a set of manifest predictors and a latent trait assumed to be measured by a set of k dichotomous items. Usually the estimated subject parameters of latent trait models are biased, especially for short tests. Therefore, the relation between a latent trait and a set of predictors should not be estimated with a regression model in which the estimated subject parameters are used as a dependent variable. Direct estimation of the relation between the latent trait and one or more independent variables is suggested instead. Estimation methods and test statistics for the Rasch model are discussed and the model is illustrated with simulated and empirical data.

Keywords

latent traitRasch modellogistic regressionconditional marginal likelihood
Type
Original Paper
Information
Psychometrika , Volume 56 , Issue 4 , December 1991 , pp. 589 - 600
Copyright
Copyright © 1991 The Psychometric Society

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