Dear Wilhelm There is an article, including a part about fitting linear mixed models. There the problem with the degrees of freedom is described. You can have a look to the second link, too, discussing the problem as well.
http://cran.r-project.org/doc/Rnews/Rnews_2005-1.pdf http://finzi.psych.upenn.edu/R/Rhelp02a/archive/67414.html Regards, Christoph Buser -------------------------------------------------------------- Christoph Buser <[EMAIL PROTECTED]> Seminar fuer Statistik, LEO C13 ETH (Federal Inst. Technology) 8092 Zurich SWITZERLAND phone: x-41-44-632-4673 fax: 632-1228 http://stat.ethz.ch/~buser/ -------------------------------------------------------------- Wilhelm B. Kloke writes: > I have a problem moving from multistratum aov analysis to lmer. > > My dataset has observations of ampl at 4 levels of gapf and 2 levels of bl > on 6 subjects levels VP, with 2 replicates wg each, and is balanced. > > Here is the summary of this set with aov: > >> summary(aov(ampl~gapf*bl+Error(VP/(bl*gapf)),hframe2)) > > > >Error: VP > > Df Sum Sq Mean Sq F value Pr(>F) > >Residuals 5 531 106 > > > >Error: VP:bl > > Df Sum Sq Mean Sq F value Pr(>F) > >bl 1 1700 1700 37.8 0.0017 ** > >Residuals 5 225 45 > >--- > >Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > > > >Error: VP:gapf > > Df Sum Sq Mean Sq F value Pr(>F) > >gapf 3 933 311 24.2 5.3e-06 *** > >Residuals 15 193 13 > >--- > >Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > > > >Error: VP:bl:gapf > > Df Sum Sq Mean Sq F value Pr(>F) > >gapf:bl 3 93.9 31.3 3.68 0.036 * > >Residuals 15 127.6 8.5 > >--- > >Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > > > >Error: Within > > Df Sum Sq Mean Sq F value Pr(>F) > >Residuals 48 318 7 > > > This is mostly identical the analysis by BMDP 4V, except for the > Greenhouse-Geisser epsilons, which are not estimated this way. > > I have to analyse a similar dataset, which is not balanced. So I need to > change the method. Following Pinheiro/Bates p.90f, I tried > > hf2.lme <- > > lme(ampl~gapf*bl,hframe2,random=list(VP=pdDiag(~gapf*bl),bl=pdDiag(~gapf))) > and some variations of this to get the same F tests generated. At least, > I got the F-test on error stratum VP:bl this way, but not the other two: > >> anova(hf2.lme) > > numDF denDF F-value p-value > >(Intercept) 1 78 764.86 <.0001 > >gapf 3 78 17.68 <.0001 > >bl 1 5 37.81 0.0017 > >gapf:bl 3 78 2.99 0.0362 > > Then I tried to move to lmer. > I tried to find something equivalent to the above lme call, with no > success at all. > > In case, that the problem is in the data, here is the set: > > VP ampl wg bl gapf > 1 WJ 22 w s 144 > 2 CR 23 w s 144 > 3 MZ 25 w s 144 > 4 MP 34 w s 144 > 5 HJ 36 w s 144 > 6 SJ 26 w s 144 > 7 WJ 34 w s 80 > 8 CR 31 w s 80 > 9 MZ 33 w s 80 > 10 MP 36 w s 80 > 11 HJ 37 w s 80 > 12 SJ 32 w s 80 > 13 WJ 34 w s 48 > 14 CR 37 w s 48 > 15 MZ 38 w s 48 > 16 MP 38 w s 48 > 17 HJ 40 w s 48 > 18 SJ 32 w s 48 > 19 WJ 36 w s 16 > 20 CR 40 w s 16 > 21 MZ 39 w s 16 > 22 MP 40 w s 16 > 23 HJ 40 w s 16 > 24 SJ 38 w s 16 > 25 WJ 16 g s 144 > 26 CR 28 g s 144 > 27 MZ 18 g s 144 > 28 MP 33 g s 144 > 29 HJ 37 g s 144 > 30 SJ 28 g s 144 > 31 WJ 28 g s 80 > 32 CR 33 g s 80 > 33 MZ 24 g s 80 > 34 MP 34 g s 80 > 35 HJ 36 g s 80 > 36 SJ 30 g s 80 > 37 WJ 32 g s 48 > 38 CR 38 g s 48 > 39 MZ 34 g s 48 > 40 MP 37 g s 48 > 41 HJ 39 g s 48 > 42 SJ 30 g s 48 > 43 WJ 36 g s 16 > 44 CR 34 g s 16 > 45 MZ 36 g s 16 > 46 MP 40 g s 16 > 47 HJ 40 g s 16 > 48 SJ 36 g s 16 > 49 WJ 22 w b 144 > 50 CR 24 w b 144 > 51 MZ 20 w b 144 > 52 MP 26 w b 144 > 53 HJ 22 w b 144 > 54 SJ 16 w b 144 > 55 WJ 26 w b 80 > 56 CR 24 w b 80 > 57 MZ 26 w b 80 > 58 MP 27 w b 80 > 59 HJ 26 w b 80 > 60 SJ 18 w b 80 > 61 WJ 28 w b 48 > 62 CR 23 w b 48 > 63 MZ 28 w b 48 > 64 MP 29 w b 48 > 65 HJ 27 w b 48 > 66 SJ 24 w b 48 > 67 WJ 32 w b 16 > 68 CR 26 w b 16 > 69 MZ 30 w b 16 > 70 MP 28 w b 16 > 71 HJ 30 w b 16 > 72 SJ 22 w b 16 > 73 WJ 22 g b 144 > 74 CR 18 g b 144 > 75 MZ 18 g b 144 > 76 MP 26 g b 144 > 77 HJ 22 g b 144 > 78 SJ 18 g b 144 > 79 WJ 24 g b 80 > 80 CR 26 g b 80 > 81 MZ 30 g b 80 > 82 MP 26 g b 80 > 83 HJ 26 g b 80 > 84 SJ 24 g b 80 > 85 WJ 28 g b 48 > 86 CR 28 g b 48 > 87 MZ 27 g b 48 > 88 MP 30 g b 48 > 89 HJ 26 g b 48 > 90 SJ 16 g b 48 > 91 WJ 28 g b 16 > 92 CR 19 g b 16 > 93 MZ 24 g b 16 > 94 MP 32 g b 16 > 95 HJ 30 g b 16 > 96 SJ 22 g b 16 > -- > Dipl.-Math. Wilhelm Bernhard Kloke > Institut fuer Arbeitsphysiologie an der Universitaet Dortmund > Ardeystrasse 67, D-44139 Dortmund, Tel. 0231-1084-257 > > ______________________________________________ > [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
