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Melk
Lapis Lazuli | Level 10

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?

5 REPLIES 5
Reeza
Super User
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.
Melk
Lapis Lazuli | Level 10
Is this what they call negative confounding?
PaigeMiller
Diamond | Level 26

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.

--
Paige Miller
Melk
Lapis Lazuli | Level 10
Hm. What do you normally use? LASSO?
PaigeMiller
Diamond | Level 26

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."

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Paige Miller

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