This chapter provides an answer to the question: What it is, philosophically speaking, to choose a model in a statistical procedure, and what does this amounts to in the context of a Bayesian inference? Special attention is given to Bayesian model selection, specifically the choice between inequality constrained and unconstrained models based on their Bayes factors and posterior model probabilities.

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Romeijn, J.-W., & Van de Schoot, R. (2008). A philosopher's view on Bayesian evaluation of informative hypotheses. In H. Hoijtink, I. Klugkist & P. Boelen (Eds.), Bayesian evaluation of informative hypotheses (pp. 329-358). New York: Springer.

ISBN: 978-0-387-09611-7