[R] too many var in lm

[carol white]

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.Vettorazzi at uke.uni-hamburg.de>
To: carol white <wht_crl at yahoo.com>
Cc: "r-help at stat.math.ethz.ch" <r-help at 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
> 
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-- 
Eik Vettorazzi

Department of Medical Biometry and Epidemiology
University Medical Center Hamburg-Eppendorf

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