Careful with those priors: A note on Bayesian estimation in two-parameter logistic item response theory models

KM Marcoulides - Measurement: Interdisciplinary Research and …, 2018 - Taylor & Francis
Measurement: Interdisciplinary Research and Perspectives, 2018Taylor & Francis
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 …
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.
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