Logistic regression problem
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. economy. Frank Harrell
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 predictor... Any suggestion is welcomed
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University