I am hoping to get some advise on the following:
I am looking for an automatic variable selection procedure to reduce the
number of potential predictor variables (~ 50) in a multiple regression
model.
I would be interested to use the forward stepwise regression using the
partial F test. I have looked into possible R-functions but could not find this
particular approach. There is a function (stepAIC) that uses the Akaike criterion or Mallow's
Cp criterion. In addition, the drop1 and add1 functions came closest to what I want
but with them I cannot perform the required procedure. Do you have any ideas? Kind regards,
Robin Smit
--------------------------------------------
Business Unit TNO Automotive
Environmental Studies & Testing
PO Box 6033, 2600 JA Delft
THE NETHERLANDS
Robin,
If you are looking for a method that does not offer the best predictive accuracy and that violates every aspect of statistical inference, you are on the right track. See http://www.stata.com/support/faqs/stat/stepwise.html for details.
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Frank E Harrell Jr Professor and Chair School of Medicine
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