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: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Diego Vázquez > Sent: Monday, May 15, 2006 11:53 AM > To: [email protected] > 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 Vázquez > Instituto Argentino de Investigaciones de las Zonas Áridas > Centro Regional de Investigaciones Científicas y Tecnológicas > CC 507, (5500) Mendoza, Argentina > http://www.cricyt.edu.ar/interactio/dvazquez/ > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
