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Model selection is a problem of judging which model from some set performs best. Popular methods include $R^2$, AIC and BIC criteria, test sets, and cross-validation. To some extent, feature selection is a subproblem of model selection.

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Intrepretation of a term that is insiginficant but which when removed causes a significant i...

I began with a maximal model which looked something like this: Response ~ Predictor 1 + Predictor 2 + Predictor 3 I used backwards stepwise elimination and likeilhood ratio tests to then try and find …