= Conditional versus marginal posterior predictive checks
In a <hierarchical Bayesian model>, replication conditional on fitted observation-level <random effects> checks the sampling layer. Replication with fresh random effects drawn from their population law also checks the population mean and variation. To assess a dose-response curve, sample the global parameters from their <posterior distribution>, draw fresh effects for new plates at each existing dose, and compare replicated means, spreads and trend discrepancies with the observed values. Reusing the fitted plate effects can conceal a misspecified mean curve by reproducing deviations those effects already absorbed.
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