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.

Data analysts sometimes report (and more often produce) results from many alternative models with different explanatory variables, functional forms, observations, or exogeneity assumptions. Classical ...