Noobie question, regression across levels

This is what I ended up using:

Data.subset<-data.frame(PlotFinal,YearFinal,BioFinal,ritFinal)     ###Subset
of main dataset
Data.length<-sapply(split(Data.subset,PlotFinal),nrow)       ### The number
of data points in each plot 

Data.sub<-split(Data.subset,PlotFinal)         ##Split Data.subset by
PlotFinal
Good.levels<-Data.sub[Data.length>10]       ##Take only those Plots that
have >10 years of observation

lmfun<-function(Good.levels)
{lm(ritFinal~BioFinal+YearFinal,data=Good.levels)}   ##Set up the 
###regression function
lmList<-lapply(Good.levels,lmfun)                       ###Apply above
function to all "good levels"

coef.List<-lapply(lmList,coef)          ###List of the coefficients of EACH
above regression

This seems to have worked beautifully.
So, my current problem is extracting the coefficients from "coef.List" (and
I think this is getting to the roof of my general confusion). coef.List
seems to be a list of a list of lm objects, right? How come them I cannot
call them by their position directly (ie. coef.List[1] gives me the first lm
object. I cannot seem to call the first coefficient in this object (the
intercept).) 
My goal is to have a bunch of new lists, each one listing a subset of
coefficients from each regression (ie. one will be a list of all the
intercepts, another the mean of all the "YearFinal" effects, etc).

Thanks again in advance for help with all these noobie questions!

AllenL wrote:

Much thanks! This helped a lot. Another quick one:
In using the lmList function in the nlme package, is it possible to
subset my data according to the number of observations in each level?
(ie. I obviously want to include only those levels in which the
observations are of sufficient size for regression). What is the best way
to exclude factors of insufficient size? Can I do it inside the lmList
function? I've read the requisite help files etc. and two hours later am
still confused.
Thanks in advance,
Allen

 Don't know if you can do it directly in lmList, but:

splitdat <- split(mydata,splitfactor)
lengths <- sapply(splitdat,nrow)  ## NOT sapply(splitdat,length)
splitdat <- splitdat[lengths>minlength]
lmfun <- function(d) { lm(y~x,data=d) }
myLmList <- lapply(splitdat,lmfun) 

OR

lengths <- sapply(split(mydata,splitfactor),nrow)
badlevels <- levels(splitfactor)[lengths<minlength]
subdata <- subset(mydata,!splitfactor %in% badlevels)

  and then proceed with lmList

  of course, I didn't test any of this ...

 Ben Bolker

View this message in context: http://www.nabble.com/Noobie-question%2C-regression-across-levels-tp21020222p21063210.html
Sent from the R help mailing list archive at Nabble.com.