[R] Logistic regression problem
Frank E Harrell Jr
f.harrell at vanderbilt.edu
Tue Sep 30 22:54:02 CEST 2008
Milicic B. Marko wrote:
> The only solution I can see is fitting all possib le 2 factor models enabling
> interactions and then assessing if interaction term is significant...
> any more ideas?
Please don't suggest such a thing unless you do simulations to back up
its predictive performance, type I error properties, and the impact of
collinearities. You'll find this approach works as well as the U.S.
> Milicic B. Marko wrote:
>> I have a huge data set with thousands of variable and one binary
>> variable. I know that most of the variables are correlated and are not
>> good predictors... but...
>> It is very hard to start modeling with such a huge dataset. What would
>> be your suggestion. How to make a first cut... how to eliminate most
>> of the variables but not to ignore potential interactions... for
>> example, maybe variable A is not good predictor and variable B is not
>> good predictor either, but maybe A and B together are good
>> Any suggestion is welcomed
>> R-help at r-project.org mailing list
>> PLEASE do read the posting guide
>> and provide commented, minimal, self-contained, reproducible code.
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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