Any Markov chain simulation is conditional on an assumed model. As the applied chapters of this book these models can be complicated and generally rely on inherently unverifiable assumptions. From a practical standpoint, it is important both to explore how inferences of substantive interest depend on such assumptions, and to check these aspects of the model whenever feasible.