[R] proc mixed vs. lme
Douglas Bates
bates at stat.wisc.edu
Wed Oct 9 17:21:55 CEST 2002
"Grathwohl,Dominik,LAUSANNE,NRC/NT" <dominik.grathwohl at rdls.nestle.com> writes:
> Hallo Peter,
>
> Thank you for the advice, now I have to update my table:
>
> SAS R
> random statement random subj(program); random = ~ 1 |
> Subj
> -2*loglik 1420.8 1420.820
> random effects
> variance(Intercept) 9.6033 9.603331
> variance(residual) 1.1969 1.196873
> the first 3 fixed effects
> intercept 83.0952 83.09524
> ProgramCont -3.4952 -3.49524
> ProgramRI -1.9702 -1.97024
> ... ... ...
>
> Everything looks nice. Perhaps Douglas could update the help file in
> SASmixed,
> where I copied the misleading code!
Umm, my version of that help file has
\examples{
options(
contrasts = c(unordered = "contr.SAS", ordered = "contr.poly"))
data(Weights)
fm1Weight <- lme( strength ~ Program * Time,
data = Weights, random = ~ 1 | Subj)
summary( fm1Weight ) # compare with output 3.1, p. 91
VarCorr( fm1Weight )
anova( fm1Weight )
fm2Weight <- update( fm1Weight, random = ~ Time | Subj )
anova( fm1Weight, fm2Weight )
summary( fm2Weight )
VarCorr( fm2Weight )
intervals( fm2Weight )
}
Notice the first line.
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