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2 results

An Analysis of Item Response Theory and Rasch Models Based on the Most Probable Distribution Method
Stefano Noventa, Luca Stefanutti, Giulio Vidotto
Journal:

Psychometrika / Volume 79 / Issue 3 / July 2014

Published online by Cambridge University Press:

01 January 2025, pp. 377-402
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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.

A Derivation of the Polytomous Rasch Model Based on the Most Probable Distribution Method
Stefano Noventa, Luca Stefanutti, Giulio Vidotto
Journal:

The Spanish Journal of Psychology / Volume 17 / 2014

Published online by Cambridge University Press:

17 November 2014, E84
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Boltzmann’s most probable distribution method is applied to derive the Polytomous Rasch model as the distribution accounting for the maximum number of possible outcomes in a test while introducing latent traits, item characteristics, and thresholds as constraints to the system. Affinities and similarities of the present result with other derivations of the model are discussed in light of the conceptual frameworks of statistical physics and of the principle of maximum entropy.

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