Thanks for your all replies. Actually, I have more than this number of variables. I want to make a selection of variables with anova and I thought that I can apply anova to the object obtained by lm. The purpose is to select the genes discriminting control samples from disease. Best,
Carol ----- Original Message ----- From: Eik Vettorazzi <e.vettora...@uke.uni-hamburg.de> To: carol white <wht_...@yahoo.com> Cc: "r-h...@stat.math.ethz.ch" <r-h...@stat.math.ethz.ch> Sent: Wednesday, August 17, 2011 3:39 PM Subject: Re: [R] too many var in lm Hi Carol, it might be another question if it is sensible to use 2100 regression parameters, but you can use . to regress one response against all other variables in a data frame as in: lm(formula = mpg ~ ., data = mtcars) and you can even exclude specific variables using "-" lm(formula = mpg ~ . - wt, data = mtcars) cheers. Am 17.08.2011 15:23, schrieb carol white: > Hello, > It might be an easy question but if you have many variables to fit in the lm > function, how do you take all without specifying var1+var2+...+var2100 in the > terms parameter in response ~ terms? > > Cheers, > > Carol > > ______________________________________________ > 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. -- Eik Vettorazzi Department of Medical Biometry and Epidemiology University Medical Center Hamburg-Eppendorf Martinistr. 52 20246 Hamburg T ++49/40/7410-58243 F ++49/40/7410-57790 ______________________________________________ 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.
