[R] linear model in the repeated data type~

[Moshe Olshansky]

Try something like this:

fits <- list(500)
for (i in 1:500)
{
if (sum(table1$id == i) == 0) fits[[i]] <- NA
else fits[[i]] <- lm(y~t,data=table1,subset=(id==i))
}


--- On Wed, 4/6/08, Manli Yan <manliyanrhelp at gmail.com> wrote:

> From: Manli Yan <manliyanrhelp at gmail.com>
> Subject: [R] linear model in the repeated data type~
> To: r-help at r-project.org
> Received: Wednesday, 4 June, 2008, 2:06 PM
> 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?
> 
> 	[[alternative HTML version deleted]]
> 
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