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An Analysis of Item Response Theory and Rasch Models Based on the Most Probable Distribution Method

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  • Stefano Noventa
  • Luca Stefanutti
  • Giulio Vidotto

Abstract

The most probable distribution method is applied to derive the logistic model as the distribution accounting for the maximum number of possible outcomes in a dichotomous test while introducing latent traits and item characteristics as constraints to the system. The item response theory logistic models, with a particular focus on the one-parameter logistic model, or Rasch model, and their properties and assumptions, are discussed for both infinite and finite populations. Copyright The Psychometric Society 2014

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  • Stefano Noventa & Luca Stefanutti & Giulio Vidotto, 2014. "An Analysis of Item Response Theory and Rasch Models Based on the Most Probable Distribution Method," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 377-402, July.
    • Handle: RePEc:spr:psycho:v:79:y:2014:i:3:p:377-402
    DOI: 10.1007/s11336-013-9348-y
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    References listed on IDEAS

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    Cited by:

    1. Stefano Noventa & Andrea Spoto & Jürgen Heller & Augustin Kelava, 2019. "On a Generalization of Local Independence in Item Response Theory Based on Knowledge Space Theory," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 395-421, June.

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