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A Comparison of the Rasch Model and Constrained Item Response Theory Models for Pertinent Psychological Test Data

  • Klaus D. Kubinger
  • Clemens Draxler
Chapter
Part of the Statistics for Social and Behavioral Sciences book series (SSBS)

Abstract

This paper provides an application of a generalization of the dichotomous Rasch model (RM) to the study of guessing behavior of respondents to typical achievement tests. One of the models applied is a constrained version of the 3PL model where a lower asymptote parameter is assumed in order to account for guessing behavior, but no variation of item discrimination is modeled. In addition, an application of mixture-distribution RMs aimed at modeling guessing effects and a comparison of the two approaches is presented. If such a constrained 3PL model is applied, in particular, to tests consisting of multiplechoice formatted items, the lower asymptote parameter can be interpreted as a guessing parameter. Therefore, the model is called the difficulty plus guessing PL (DGPL) model. An empirical example shows that a multiplechoice item pool only fits the Rasch model after a large number of items have been deleted, while the DGPL model can save most of those deleted items as it takes the severe but item-specific guessing effects into consideration. Furthermore, multiclass mixed RM analyses show — in comparison to the Rasch model — a good fit of the data and confirm item-specific guessing effects.

Keywords

Model Check Item Parameter Marginal Likelihood Item Pool Person Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science + Business Media, LLC 2007

Authors and Affiliations

  • Klaus D. Kubinger
    • 1
  • Clemens Draxler
    • 2
  1. 1.Vienna UniversityWienAustria
  2. 2.Leibniz Institute for Science EducationKielGermany

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