Hi Bill, If you can put all (and only) your variables into a dataframe, (for example: X <- data.frame(y, x1, x2, x3) )
then another alternative to David's solution would be: lm(y ~ .^3, data = X) '.' will expand to every column except y, and then the ^3 will get you up to 3-way interactions. Cheers, Josh On Sun, Dec 5, 2010 at 12:19 PM, William Simpson <william.a.simp...@gmail.com> wrote: > Suppose I have x variables x1, x2, x3 (however in general I don't know > how many x variables there are). I can do > X<-cbind(x1,x2,x3) > lm(y ~ X) > This fits the no-interaction model with b0, b1, b2, b3. > > How can I get lm() to fit the model that includes interactions when I > pass X to lm()? For my example, > lm(y~x1*x2*x3) > I am looking for something along the lines of > lm(y~X ...) > where ... is some extra stuff I need to fill in. > > Thanks for any help. > Bill > > ______________________________________________ > 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. > -- Joshua Wiley Ph.D. Student, Health Psychology University of California, Los Angeles http://www.joshuawiley.com/ ______________________________________________ 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.