Re: [R] Linear regression on several groups

2010-08-13 Thread Allan Engelhardt

 Please read the posting guide and include a standalone example.

Maybe you want something like the results from

lm(weight ~ Time, data = ChickWeight, subset = Diet==1)
lm(weight ~ Time, data = ChickWeight, subset = Diet==2)
## ... etc ...

Then you could do

(m - lm(weight ~ Time*Diet, data = ChickWeight))

To get the Diet==2 coefficients from above you could use something like

sum(coef(m)[c((Intercept), Diet2)])  # Intercept
sum(coef(m)[c(Time, Time:Diet2)])# Slope

Hope this helps a little.

Allan

On 12/08/2010 17:11, JesperHybel wrote:

I have a simple dataset of a numerical dependent Y, a numerical independent X
and a categorial variable Z with three levels. I want to do linear
regression Y~X for each level of Z. How can I do this in a single command
that is without using lm() applied three isolated times?


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Re: [R] Linear regression on several groups

2010-08-13 Thread Eik Vettorazzi
hi,
maybe an ANCOVA is what you want, which is also done by lm in R

lm(y~x*z)



Am 12.08.2010 17:11, schrieb JesperHybel:
 
 I have a simple dataset of a numerical dependent Y, a numerical independent X
 and a categorial variable Z with three levels. I want to do linear
 regression Y~X for each level of Z. How can I do this in a single command
 that is without using lm() applied three isolated times?


-- 
Eik Vettorazzi
Institut für Medizinische Biometrie und Epidemiologie
Universitätsklinikum Hamburg-Eppendorf

Martinistr. 52
20246 Hamburg

T ++49/40/7410-58243
F ++49/40/7410-57790

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Re: [R] Linear regression on several groups

2010-08-13 Thread JesperHybel

Example is spot on - sr for not providing one myself.
The results you calculate are what I'm looking for.

Would like a function F where I could type:

F(weight ~ Time, data = ChickWeight, SOME ARGUMENT = Diet))

Resulting in

for (i in 1:4){
print(

lm(weight ~ Time, data = ChickWeight, subset = Diet==i)

)
}

I'm simply trying to minimize amount of looping and typing etc.

BR Jesper




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Re: [R] Linear regression on several groups

2010-08-13 Thread Derek Ogle
Have a look at lmList() in the nlme package.

 -Original Message-
 From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
 project.org] On Behalf Of JesperHybel
 Sent: Friday, August 13, 2010 7:56 AM
 To: r-help@r-project.org
 Subject: Re: [R] Linear regression on several groups
 
 
 Example is spot on - sr for not providing one myself.
 The results you calculate are what I'm looking for.
 
 Would like a function F where I could type:
 
 F(weight ~ Time, data = ChickWeight, SOME ARGUMENT = Diet))
 
 Resulting in
 
 for (i in 1:4){
 print(
 
 lm(weight ~ Time, data = ChickWeight, subset = Diet==i)
 
 )
 }
 
 I'm simply trying to minimize amount of looping and typing etc.
 
 BR Jesper
 
 
 
 
 --
 View this message in context: http://r.789695.n4.nabble.com/Linear-
 regression-on-several-groups-tp2322835p2324154.html
 Sent from the R help mailing list archive at Nabble.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.

__
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] Linear regression on several groups

2010-08-12 Thread JesperHybel

I have a simple dataset of a numerical dependent Y, a numerical independent X
and a categorial variable Z with three levels. I want to do linear
regression Y~X for each level of Z. How can I do this in a single command
that is without using lm() applied three isolated times?
-- 
View this message in context: 
http://r.789695.n4.nabble.com/Linear-regression-on-several-groups-tp2322835p2322835.html
Sent from the R help mailing list archive at Nabble.com.

__
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.