Five variable selection methods are available. The simplest method (and the default) is SELECTION=NONE, for which PROC PHREG fits the complete model as specified in the MODEL statement. The other four ...

In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to ...

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.

The nine methods of model selection implemented in PROC REG are specified with the SELECTION= option in the MODEL statement. Each method is discussed in this section. This method is the default and ...

Suppose we observe samples of a subset of a collection of random variables. No additional information is provided about the number of latent variables, nor of the relationship between the latent and ...