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Fully Gibbs Sampling Algorithms for Bayesian Variable Selection in Latent Regression Models
This study proposed efficient Gibbs sampling algorithms with different types of shrinkage priors for variable selection in a latent regression model under a unidimensional two-parameter logistic item response theory model.
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Fully Gibbs Sampling Algorithms for Bayesian Variable Selection in Latent Regression Models