Publications

Ignorable Problem, Outing Notable Solution

Bruce Ratner, Ph.D.

Variable selection in regression - identifying the best subset among many variables to include in a model - is arguably the hardest part of model building. Many variable selection methods exist. Many statisticians know them, but few know they produce poorly performing models. The wanting variable selection methods are a miscarriage of statistics because they are developed by debasing sound statistical theory into a misguided pseudo-theoretical foundation.

The purpose of this article is two-fold:

1) To resurface the scope of literature on the weaknesses of variable selection meth-ods.

2) To enliven anew a notable solution to defining a substantially performing regression model.

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