Dear Gurus, Thank you in advance for your assistance. I'm trying to understand scope better when performing stepwise regression using "step." I have a model with a binary response variable and 10 predictor variables. When I perform stepwise regression I define scope=.^2 to allow interactions between all terms. But I am missing something. When I perform stepwise regression (both directions) on the main model (y~x1+x2+…+x10) the method returns quickly with an answer; however, when I define all interactions in the main model (y~x1+x2+…+x10+x1:x2+x1:x3+…) and then perform stepwise regression (backward only) it runs so long I have to kill it.
So here's my question: what is the difference between scope=.^2 on the additive (proper term?) model and defining all interactions and doing backward regression? My understanding is that .^2 is supposed to allow all interactions! Thank you for your help. Mark ______________________________________________ R-help@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.
