topic Re: Automated variable selection in SAS Programming

Automated variable selection

Melk — Tue, 14 Jul 2020 15:56:42 GMT

Hi All,

I am used the automated variable selection (stepwise method) with a SLE of 0.2 and a SLS of 0.05. I am getting variables in my final model that are >0.20 in my univariate analysis. I am wondering why that is, is it because those variables are significant in the presence of other variables and they get entered in one of the middle steps?

Re: Automated variable selection

Reeza — Tue, 14 Jul 2020 16:02:16 GMT

Yes. This is why the univariate method of variable selection is not considered a reliable or acceptable method to determine which variables to include in your regression model.

Re: Automated variable selection

Melk — Tue, 14 Jul 2020 16:16:56 GMT

Is this what they call negative confounding?

Re: Automated variable selection

PaigeMiller — Tue, 14 Jul 2020 16:25:18 GMT

There are a lot of criticisms of stepwise, I assume this is one of the 12,631 reasons why you shouldn't use Stepwise. If you go to your favorite internet search engine and type in "problems with stepwise regression", you will find enough to read for a week.

So, don't use stepwise.

Re: Automated variable selection

Melk — Tue, 14 Jul 2020 16:30:08 GMT

Hm. What do you normally use? LASSO?

Re: Automated variable selection

PaigeMiller — Tue, 14 Jul 2020 16:35:05 GMT

I use Partial Least Squares regression (PROC PLS), which works well in the presence of multicollinearity. According to this article, "Partial least squares (PLS) is a method for constructing predictive models when the factors are many and highly collinear."