Careful with Those Priors: A Note on Bayesian Estimation in Two-Parameter Logistic Item Response Theory Models

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Abstract

This study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that the Bayesian estimates obtained with both informative and non-informative priors exhibited varying levels of bias ranging in most cases from moderate to severe bias. Results are discussed in light of these findings and recommendations concerning the use of priors in empirical research are provided.

Original languageEnglish (US)
Pages (from-to)92-99
Number of pages8
JournalMeasurement
Volume16
Issue number2
DOIs
StatePublished - Apr 3 2018
Externally publishedYes

Keywords

  • Bayesian analysis
  • Informative priors
  • diffuse priors
  • two parameter logistic model

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