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Posterior Predictive Model Checking for DCM

The method compares the observed data with replicated data (data that are generated or predicted by the model) using a number of diagnostic measures that are sensitive to model misfit. Any systematic differences between aspects of the observed data set and those of the replicated data sets indicate a failure of the model to explain those aspects of the data. Graphical display is the most natural and easily comprehensible way to perform posterior predictive checks (PPC); in situations where graphical displays do not suffice or are cumbersome (e.g., for too many checks simultaneously), one can also use a tail-area probability, also known as a posterior predictive p-value (PPP-value).