The purpose of statistical model selection is to identify a parsimonious model, which is a model that is as simple as possible while maintaining good predictive ability over the outcome of interest.

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Bayesian model selection provides a coherent framework for comparing competing statistical models by balancing goodness of fit against model complexity through the use of prior distributions and ...