On Aug 17, 2011, at 10:39 AM, carol white wrote:
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.
You need to consult a statistician with experience in this area.
--
David.
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
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--
Eik Vettorazzi
Department of Medical Biometry and Epidemiology
University Medical Center Hamburg-Eppendorf
Martinistr. 52
20246 Hamburg
T ++49/40/7410-58243
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David Winsemius, MD
West Hartford, CT
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