[R] library(car): Anova and repeated measures without between subjects factors
John Fox
jfox at mcmaster.ca
Tue Oct 16 21:04:51 CEST 2007
Dear Ralf,
Unfortunately, Anova.mlm(), and indeed Anova() more generally, won't
handle a model with only a constant. As you point out, this isn't
reasonable for repeated-measures ANOVA, where it should be possible to
have only within-subjects factors. When I have a chance, I'll see what
I can do to fix the problem -- my guess is that it shouldn't be too
hard.
Thanks for pointing out this limitation in Anova.mlm()
John
On Tue, 16 Oct 2007 17:20:07 +0200
Ralf Goertz <R_Goertz at web.de> wrote:
> Hi,
>
> sorry if this is explained somewhere but I didn't find anything.
>
> How can I use "Anova" from the car package to test a modell without
> between subject's factors? Suppose I have the following data
>
> mat.1 mat.2 mat.3 di ex
> 1 85 85 88 1 1
> 2 90 92 93 1 1
> 3 97 97 94 1 1
> 4 80 82 83 1 1
> 5 91 92 91 1 1
> 6 83 83 84 2 1
> 7 87 88 90 2 1
> 8 92 94 95 2 1
> 9 97 99 96 2 1
> 10 100 97 100 2 1
> 11 86 86 84 1 2
> 12 93 103 104 1 2
> 13 90 92 93 1 2
> 14 95 96 100 1 2
> 15 89 96 95 1 2
> 16 84 86 89 2 2
> 17 103 109 90 2 2
> 18 92 96 101 2 2
> 19 97 98 100 2 2
> 20 102 104 103 2 2
> 21 93 98 110 1 3
> 22 98 104 112 1 3
> 23 98 105 99 1 3
> 24 87 132 120 1 3
> 25 94 110 116 1 3
> 26 95 126 143 2 3
> 27 100 126 140 2 3
> 28 103 124 140 2 3
> 29 94 135 130 2 3
> 30 99 111 150 2 3
>
> Using
>
> >
>
Anova(lm(mat~di*ex,data=data),idata=data.frame(zeit=ordered(1:3)),idesign=~zeit)
>
> Type II Repeated Measures MANOVA Tests: Pillai test statistic
> Df test stat approx F num Df den Df Pr(>F)
> di 1 0.377 14.524 1 24 0.0008483 ***
> ex 2 0.800 47.915 2 24 4.166e-09 ***
> di:ex 2 0.281 4.695 2 24 0.0190230 *
> zeit 1 0.782 41.209 2 23 2.491e-08 ***
> di:zeit 1 0.252 3.865 2 23 0.0357258 *
> ex:zeit 2 0.836 8.611 4 48 2.538e-05 ***
> di:ex:zeit 2 0.518 4.189 4 48 0.0054586 **
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> works as expected. But every once in a while I have a model without
> between subject's factors. So I thought of
>
> >
>
Anova(lm(mat~1,data=data),idata=data.frame(zeit=factor(1:3)),idesign=~zeit)
> Fehler in L %*% B : nicht passende Argumente
>
> (Error in L %*% B : non matching arguments)
>
> On the other hand using anova.mlm I get
>
> >
>
anova.mlm(lm(mat~1,data),idata=data.frame(zeit=factor(1:3)),X=~1,test="Spherical")
> Analysis of Variance Table
>
>
> Contrasts orthogonal to
> ~1
>
> Greenhouse-Geisser epsilon: 0.7464
> Huynh-Feldt epsilon: 0.7777
>
> Df F num Df den Df Pr(>F) G-G Pr H-F Pr
> (Intercept) 1 11.767 2 58 5.1375e-05 3.1183e-04 2.4939e-04
> Residuals 29
>
>
> How can achieve this with Anova?
>
>
> Thanks in advance,
>
> Ralf
>
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--------------------------------
John Fox, Professor
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
http://socserv.mcmaster.ca/jfox/
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