The issue is not unresolved within lmer, but with the statistical model itself.
SAS gives you alternatives for the ddf such as Kenward-Roger. But, as I have
noted on the list before, this makes the assumption that the ratio of the
variances follow an F distribution and that the only remaining challenge is to
then estimate the ddf. Then, one can get all the p-values you want.
If you believe that is true, then the SAS options will give you some statistics
to use--not to say that they are correct, though.
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Diego V?zquez
> Sent: Monday, May 15, 2006 11:53 AM
> To: r-help at stat.math.ethz.ch
> Subject: [R] anova statistics in lmer
>
> Dear list members,
>
> I am new to R and to the R-help list. I am trying to perform
> a mixed-model analysis using the lmer() function. I have a
> problem with the output anova table when using the anova()
> function on the lmer output object: I only get the numerator
> d.f., the sum of squares and the mean squares, but not the
> denominator d.f., F statistics and P values.
> Below is a sample output, following D. Bates' SASmixed
> example in his paper "Fitting linear mixed models in R"
> (R-News 5: 27-30).
>
> By reading the R-help archive, I see that this problem has
> come up before (e.g.,
> http://tolstoy.newcastle.edu.au/R/help/06/04/25013.html).
> What I understand from the replies to this message is that
> this incomplete output results from some unresolved issues
> with lmer, and that it is currently not possible to use it to
> obtain full anova statistics. Is this correct? And is this
> still unresolved? If so, what is the best current alternative
> to conduct a mixed model analysis, other than going back to SAS?
>
> I would greatly appreciate some help.
>
> Diego
>
> ----
>
> Example using SASmixed "HR" data (see D. Bates, "Fitting
> linear mixed models in R", R-News 5: 27-30)
>
> > data("HR",package="SASmixed")
> > library(lme4)
> Loading required package: Matrix
> Loading required package: lattice
>
> Attaching package: 'lattice'
>
>
> The following object(s) are masked from package:Matrix :
>
> qqmath
>
> > (fm1<-lmer(HR~baseHR+Time*Drug+(1|Patient),HR))
> Linear mixed-effects model fit by REML
> Formula: HR ~ baseHR + Time * Drug + (1 | Patient)
> Data: HR
> AIC BIC logLik MLdeviance REMLdeviance
> 788.6769 810.9768 -386.3384 791.8952 772.6769
> Random effects:
> Groups Name Variance Std.Dev.
> Patient (Intercept) 44.541 6.6739
> Residual 29.780 5.4571
> number of obs: 120, groups: Patient, 24
>
> Fixed effects:
> Estimate Std. Error t value
> (Intercept) 33.96209 9.93059 3.4199
> baseHR 0.58819 0.11846 4.9653
> Time -10.69835 2.42079 -4.4194
> Drugb 3.38013 3.78372 0.8933
> Drugp -3.77824 3.80176 -0.9938
> Time:Drugb 3.51189 3.42352 1.0258
> Time:Drugp 7.50131 3.42352 2.1911
>
> Correlation of Fixed Effects:
> (Intr) baseHR Time Drugb Drugp Tm:Drgb
> baseHR -0.963
> Time -0.090 0.000
> Drugb -0.114 -0.078 0.237
> Drugp -0.068 -0.125 0.236 0.504
> Time:Drugb 0.064 0.000 -0.707 -0.335 -0.167 Time:Drugp
> 0.064 0.000 -0.707 -0.167 -0.333 0.500
> > anova(fm1)
> Analysis of Variance Table
> Df Sum Sq Mean Sq
> baseHR 1 745.99 745.99
> Time 1 752.86 752.86
> Drug 2 86.80 43.40
> Time:Drug 2 143.17 71.58
>
>
> --
> Diego V?zquez
> Instituto Argentino de Investigaciones de las Zonas ?ridas
> Centro Regional de Investigaciones Cient?ficas y Tecnol?gicas
> CC 507, (5500) Mendoza, Argentina
> http://www.cricyt.edu.ar/interactio/dvazquez/
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
>