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Missing data are nearly always an issue in longitudinal studies. This example uses the MCMC procedure to fit Bayesian logistic regression models to analyze air pollution data with missing values. A typical missing data strategy is to eliminate observations with missing data, but the resulting inference might not be valid if the observations with missing covariates are substantially different from…