[R] [r] regression coefficient for different factors

[Dimitri Liakhovitski]

First you have to create something (e.g., a list) that holds your output:

mylist<-NULL

Then you loop through the levels of c and run a regression of a onto b
(no need to include c anymore because c will have zero variance within
each level of c):
for(i in levels(c)){
  temp.data<-mydataset[mydataset$c %in% i]
  mylist[[i]]<-lm(a ~  b, data=temp.data)
}

Once you are done - you can write another loop (this time across all
elements of mylist - that will have as many elements as there are
levels in c) and extract the coefficients.
Dimitri


On Fri, May 20, 2011 at 9:57 AM, Francesco Nutini
<nutini.francesco at gmail.com> wrote:
> Yes Dimitri that's what I mean!
> Something like this?
>
> for(i in levels(c)) { lm(a ~  b *  c , data=mydataset)}
>
> And what about to see the output?
>
> Thanks!
>
>> Date: Fri, 20 May 2011 09:46:08 -0400
>> Subject: Re: [R] [r] regression coefficient for different factors
>> From: dimitri.liakhovitski at gmail.com
>> To: nutini.francesco at gmail.com
>> CC: rbaer at atsu.edu; r-help at r-project.org
>>
>> Francesco, do you just want a separate regression for each level of
>> your factor c?
>> You could write a loop - looping through levels of c:
>>
>> for(i in levels(c)){
>> select your data here and write a regression formula
>> }
>>
>> On Fri, May 20, 2011 at 9:39 AM, Francesco Nutini
>> <nutini.francesco at gmail.com> wrote:
>> >
>> > Thanks for your reply,
>> >
>> > ?summary produce a  multiple r2.
>> > My dataset il similar to this one:
>> >
>> >>            a         b   c
>> >> 1 -1.4805676 0.9729927 x
>> >> 2  1.5771695 0.2172974 x
>> >> 3 -0.9567445 0.5205087 x
>> >> 4 -0.9200052 0.8279428 z
>> >> 5 -1.9976421 0.9641110 z
>> >> 6 -0.2722960 0.6318801 y
>> >
>> > So, I would like to know the r2 for a~b for every factors levels.
>> > Off course I can made the regression separately for every factors, but
>> > my dataset have 68 factors...
>> >
>> > ----------
>> > Francesco Nutini
>> > PhD student
>> > CNR-IREA (Institute for Electromagnetic Sensing of the Environment)
>> > Milano, Italy
>> >
>> >  > From: rbaer at atsu.edu
>> >> To: nutini.francesco at gmail.com; r-help at r-project.org
>> >> Subject: Re: [R] [r] regression coefficient for different factors
>> >> Date: Fri, 20 May 2011 08:07:59 -0500
>> >>
>> >> ?summary
>> >>
>> >> produces r^2 in 2nd to last line, as in,
>> >> > set.seed(12); a=rnorm(100); b = runif(100); c = factor(rep(c('No',
>> >> > 'Yes'),50)); df = data.frame(a,b,c)
>> >> > head(df)
>> >>            a         b   c
>> >> 1 -1.4805676 0.9729927  No
>> >> 2  1.5771695 0.2172974 Yes
>> >> 3 -0.9567445 0.5205087  No
>> >> 4 -0.9200052 0.8279428 Yes
>> >> 5 -1.9976421 0.9641110  No
>> >> 6 -0.2722960 0.6318801 Yes
>> >> > mod = lm(a ~ b*c)
>> >> > summary(mod)
>> >>
>> >> Call:
>> >> lm(formula = a ~ b * c)
>> >>
>> >> Residuals:
>> >>     Min      1Q  Median      3Q     Max
>> >> -1.8196 -0.4754 -0.0246  0.5585  2.0941
>> >>
>> >> Coefficients:
>> >>             Estimate Std. Error t value Pr(>|t|)
>> >> (Intercept)   0.2293     0.2314   0.991    0.324
>> >> b            -0.4226     0.3885  -1.088    0.280
>> >> cYes          0.1578     0.3202   0.493    0.623
>> >> b:cYes       -0.5878     0.5621  -1.046    0.298
>> >>
>> >> Residual standard error: 0.8455 on 96 degrees of freedom
>> >> Multiple R-squared: 0.07385,  Adjusted R-squared: 0.04491
>> >> F-statistic: 2.552 on 3 and 96 DF,  p-value: 0.0601
>> >>
>> >> ------------------------------------------
>> >> Robert W. Baer, Ph.D.
>> >> Professor of Physiology
>> >> Kirksville College of Osteopathic Medicine
>> >> A. T. Still University of Health Sciences
>> >> 800 W. Jefferson St.
>> >> Kirksville, MO 63501
>> >> 660-626-2322
>> >> FAX 660-626-2965
>> >>
>> >>
>> >> --------------------------------------------------
>> >> From: "Francesco Nutini" <nutini.francesco at gmail.com>
>> >> Sent: Friday, May 20, 2011 4:17 AM
>> >> To: "[R] help" <r-help at r-project.org>
>> >> Subject: [R] [r] regression coefficient for different factors
>> >>
>> >> >
>> >> > Dear R-helpers,
>> >> >
>> >> > In my dataset I have two continuous variable (A and B) and one
>> >> > factor.
>> >> > I'm investigating the regression between the two variables usign the
>> >> > command
>> >> > lm(A ~ B, ...)
>> >> > but now I want to know the regression coefficient (r2) of A vs. B for
>> >> > every factors.
>> >> > I know that I can obtain this information with excel, but the factor
>> >> > have
>> >> > 68 levels...maybe [r] have a useful command.
>> >> >
>> >> > Thanks,
>> >> >
>> >> > Francesco Nutini
>> >> >
>> >> > [[alternative HTML version deleted]]
>> >> >
>> >> > ______________________________________________
>> >> > R-help at 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.
>> >> >
>> >
>> >        [[alternative HTML version deleted]]
>> >
>> > ______________________________________________
>> > R-help at 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.
>> >
>>
>>
>>
>> --
>> Dimitri Liakhovitski
>> Ninah Consulting
>> www.ninah.com
>



-- 
Dimitri Liakhovitski
Ninah Consulting
www.ninah.com