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Logistic Mixture Models

  • Jürgen Rost
Chapter

Abstract

Discrete mixture distribution models (MDM) assume that observed data do not stem from a homogeneous population of individuals but are a mixture of data from two or more latent populations (Everitt and Hand, 1981; Titterington et al., 1985). Applied to item response data this means that a particular IRT model does not hold for the entire sample but that different sets of model parameters (item parameters, ability parameters, etc.) are valid for different subpopulations.

Keywords

Mixture Model Latent Class Item Parameter Latent Class Model Ability Estimate 
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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© Springer Science+Business Media New York 1997

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  • Jürgen Rost

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