I believe your difficulties will be greatly enlightened by using
either lme in library(nlme) or lmer associated with the lme4 package.
Essential documentation is Pinheiro and Bates (2000) Mixed-Effects
Models in S and S-Plus (Springer).
hope this helps.
spencer graves
Joseph LeBouton wrote:
> Hello all,
>
> I'm trying to do a nested linear model with a dataset that incorporates
> an observation for each of several classes within each of several plots.
> I have 219 plots, and 17 classes within each plot.
>
> data.frame has columns "plot","class","age","dep.var"
>
> With lm(dep.var~class*age),
>
> The summary(lm) function returns t-test and F-test values evaluated as
> though I were working with 219*17-17=3706 degrees of freedom, when in
> fact I have but 219-17=202 df. I'm probably being dense on this one,
> but is there a way I can set df to the proper number so that summary.lm
> does the correct significance test? Or should I be doing an entirely
> different anlaysis?
>
> Thanks,
>
> -jlb
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