[R] linear model in the repeated data type~

[Austin, Matt]

How about


library(nlme)
allFits <- lmList(y ~ t|id, data=table1, pool=FALSE)

or

allFits <- by(table1, table1$id, function(x) lm(y ~ t, data=x))

Both ways store the results as a list, so you can access individual results using list extraction.


--Matt

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Manli Yan
Sent: Tuesday, June 03, 2008 9:07 PM
To: r-help at r-project.org
Subject: [R] linear model in the repeated data type~

  here is the data:
 y<-c(5,2,3,7,9,0,1,4,5)
id<-c(1,1,6,6,7,8,15,15,19)
t<-c(50,56,50,56,50,50,50,60,50)
table1<-data.frame(y,id,t)//longitudinal data

what  I want to do is to use the linear model for each id ,then get the estimate value,like:

fit1<-lm(y~t,data=table1,subset=(id==1))

but ,you can see the variable "id" is quite irregular,they are not arranaged in order and many number missing,if I write a loop by using "for",it will give me a lot "NA", and for sure ,I dont want to type id=## for about 500 times,any one know how to deal with it?

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