Hi Everyone May I request for a small help while performing the regression analysis. I would like to know is there any possibility of conducting the regression for different data subsets (in the same data file), classified on the basis of "grouping variable". The alternative for this is running the regression for n number of times which you all know is quite cumbersome. Thank you for your kind attention and help rgds krishna
help on regression by subsets in dataset
3 messages · Krishna Kumar, Dimitris Rizopoulos, Gabor Grothendieck
you could use function lmList() from the nlme package, i.e., dat <- data.frame(y = rnorm(120), x = runif(120, -3, 3), g = rep(1:3, each = 40)) ############ library(nlme) m <- lmList(y ~ x | g, data = dat) m summary(m) I hope it helps. Best, Dimitris ---- Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/16/336899 Fax: +32/16/337015 Web: http://www.med.kuleuven.be/biostat/ http://www.student.kuleuven.be/~m0390867/dimitris.htm ----- Original Message ----- From: "Krishna" <snvk4u at gmail.com> To: <r-help at stat.math.ethz.ch> Sent: Monday, August 08, 2005 12:20 PM Subject: [R] help on regression by subsets in dataset
Hi Everyone May I request for a small help while performing the regression analysis. I would like to know is there any possibility of conducting the regression for different data subsets (in the same data file), classified on the basis of "grouping variable". The alternative for this is running the regression for n number of times which you all know is quite cumbersome. Thank you for your kind attention and help rgds krishna
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On 8/8/05, Krishna <snvk4u at gmail.com> wrote:
Hi Everyone May I request for a small help while performing the regression analysis. I would like to know is there any possibility of conducting the regression for different data subsets (in the same data file), classified on the basis of "grouping variable". The alternative for this is running the regression for n number of times which you all know is quite cumbersome.
This defines a model which has a separate intercept and slope for each value of the grouping variable g:
# sample data x <- 1:12 g <- gl(4,3) g
[1] 1 1 1 2 2 2 3 3 3 4 4 4 Levels: 1 2 3 4
set.seed(1) y <- rnorm(12)
# now define the model and run the regression lm(y ~ g/x - 1)
Call:
lm(formula = y ~ g/x - 1)
Coefficients:
g1 g2 g3 g4 g1:x g2:x g3:x g4:x
-0.21697 6.40748 0.24710 -3.29170 -0.10459 -1.20787 0.04418 0.34762