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Michael Bergrab

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Review Open access Aug 2026

Bayesian model comparison for random effects probit models with missing covariates

For model comparison in random effects probit models with incompletely observed covariates, this paper develops a Bayesian data-augmentation workflow in which latent Gaussian responses, random effects, and missing covariate values are updated within a common augmented sampling scheme. Because specifying a fully param...

Michael Bergrab · 0 citations

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