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Estimating a Noncompensatory IRT Model Using Metropolis within Gibbs Sampling
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Babcock, Ben – Applied Psychological Measurement, 2011
Relatively little research has been conducted with the noncompensatory class of multidimensional item response theory (MIRT) models. A Monte Carlo simulation study was conducted exploring the estimation of a two-parameter noncompensatory item response theory (IRT) model. The estimation method used was a Metropolis-Hastings within Gibbs algorithm…
Descriptors: Item Response Theory, Sampling, Computation, Statistical Analysis
Order-Constrained Bayes Inference for Dichotomous Models of Unidimensional Nonparametric IRT
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Karabatsos, George; Sheu, Ching-Fan – Applied Psychological Measurement, 2004
This study introduces an order-constrained Bayes inference framework useful for analyzing data containing dichotomous scored item responses, under the assumptions of either the monotone homogeneity model or the double monotonicity model of nonparametric item response theory (NIRT). The framework involves the implementation of Gibbs sampling to…
Descriptors: Inferences, Nonparametric Statistics, Item Response Theory, Data Analysis