Abstract
ABSTRACTThis 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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More From: Measurement: Interdisciplinary Research and Perspectives
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