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Mixture-Distribution and HYBRID Rasch Models

  • Matthias von Davier
  • Kentaro Yamamoto
Chapter
Part of the Statistics for Social and Behavioral Sciences book series (SSBS)

Abstract

This chapter provides an overview of mixture-distribution Rasch models (RMs) and HYBRID RMs and their extensions. Discrete mixture-distribution IRT models assume that the observed data were drawn from an unobservable mixture of populations. Within each of these populations, a different item response model may hold (HYBRID models), or models with different sets of item parameters and different ability distributions may hold (mixture Rasch models, or more generally, mixture IRT models).

Keywords

Hybrid Model Class Membership Item Parameter Loglinear Model Item Response Model 
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

  • Matthias von Davier
    • 1
  • Kentaro Yamamoto
    • 1
  1. 1.Educational Testing ServicePrincetonUSA

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