[R] library(car): Anova and repeated measures without between subjects factors

[John Fox]

Dear Ralf,

Thanks for the additional suggestions -- I'll take a look at them as well.

John

--------------------------------
John Fox, Professor
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox 
-------------------------------- 

> -----Original Message-----
> From: r-help-bounces at r-project.org 
> [mailto:r-help-bounces at r-project.org] On Behalf Of Ralf Goertz
> Sent: Wednesday, October 17, 2007 6:00 AM
> To: John Fox
> Cc: r-help at r-project.org
> Subject: Re: [R]library(car): Anova and repeated measures 
> without between subjects factors
> 
> John Fox, Dienstag, 16. Oktober 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()
> 
> Dear John,
> 
> I am looking forward to your having a chance. There is one 
> thing that I would like to request, though. 
> Greenhouse-Geisser and Huyn-Feldt eps corrections have 
> already been implemented but how about Mauchly's sphericity 
> test? I know this can be done with mauchly.test() but it 
> would be nice to have it in the summary of Anova().
> 
> However, there is one more thing. Look at the following data
> 
> > c1<-c(-6.0,-10.3,-2.9,-8.3,-10.0,5.3,-7.7,-0.8,9.1,-6.2)
> > mat<-matrix(c(c1,c1),10,2)
> > mat
>        [,1]  [,2]
>  [1,]  -6.0  -6.0
>  [2,] -10.3 -10.3
>  [3,]  -2.9  -2.9
>  [4,]  -8.3  -8.3
>  [5,] -10.0 -10.0
>  [6,]   5.3   5.3
>  [7,]  -7.7  -7.7
>  [8,]  -0.8  -0.8
>  [9,]   9.1   9.1
> [10,]  -6.2  -6.2
> 
> > bf<-ordered(rep(1:2,5))
> > bf
>  [1] 1 2 1 2 1 2 1 2 1 2
> Levels: 1 < 2
> 
> Since the two columns of mat are equal:
> 
> > t.test(mat[,1],mat[,2],paired=T)
> 
>         Paired t-test
> 
> data:  mat[, 1] and mat[, 2]
> t = NaN, df = 9, p-value = NA
> alternative hypothesis: true difference in means is not equal to 0
> 95 percent confidence interval:
>  NaN NaN
> sample estimates:
> mean of the differences 
>                       0 
> 
> I would assume to either get a warning or a F-value of 0 for 
> the repeated factor zeit but actually:
> 
> > Anova(lm(mat~bf),idata=data.frame(zeit=ordered(1:2)),idesign=~zeit)
> 
> Type II Repeated Measures MANOVA Tests: Pillai test statistic
>         Df test stat approx F num Df den Df Pr(>F)
> bf       1    0.0020   0.0163      1      8 0.9016
> zeit     1    0.2924   3.3059      1      8 0.1065
> bf:zeit  1    0.0028   0.0221      1      8 0.8854
> 
> whereas
> 
> > anova.mlm(lm(mat~bf),X=~1,idata=data.frame(zeit=ordered(1:2)))
> 
> Error in anova.mlm(...) :
>  residuals have rank 1 < 2
> 
> This is quite dangerous. In a real data situation I 
> accidentally used the same column twice and I got a 
> significant effect for the factor zeit! I hope it wouldn't be 
> too hard to fix this. too.
> 
> Ralf
> 
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