Summary
In this paper, we give a description of posterior predictive checking (introduced by Rubin, 1984) for detecting departures between the data and the posited model and illustrate how the posterior predictive check can be used in practice. We further discuss interpretability, frequency properties, and prior sensitivity of the posterior predictive p-value.
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The work reported in this paper was supported in part by Grant OT/96/10 of the Research Council of the Katholieke Universiteit Leuven.
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Berkhof, J., van Mechelen, I. & Hoijtink, H. Posterior predictive checks: Principles and discussion. Computational Statistics 15, 337–354 (2000). https://doi.org/10.1007/s001800000038
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DOI: https://doi.org/10.1007/s001800000038