Hi try glm(Response~ .^2, data=yourdata.frame) For all predictors (.) and 2-way interactions (^2). You might also want to see ?drop.terms and ?formula for automating the construction of all model combinations.
Side note: R is not SAS (fortunately). Interaction is denoted ":", X*Y is shorthand for X+Y+X:Y. Your "X+Y+X*Y" is redundant. HTH On Wed, Mar 7, 2012 at 4:16 AM, Christofer Bogaso <bogaso.christo...@gmail.com> wrote: > Dear all, I was working with a GLM model and wondering whether is it > possible to have a model description with all possible main effects as > well as all interactions. Currently I do it manually however this will > become cumbersome if I have large number of variables. > > Means suppose I have 3 explanatory variables and want to feed > automatically with all possible combinations like: > > > glm(Response~1) > > glm(Response~X) > glm(Response~Y) > glm(Response~Z) > > glm(Response~X+Y) > glm(Response~X+Z) > glm(Response~Z+Y) > > glm(Response~X+Y+X*Y) > glm(Response~X+Z+X*Y) > > .................................................... all combinations > which are possible > > Thanks and regards, > > ______________________________________________ > 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. ______________________________________________ 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.
