I have design with two repeated-measures factor, and no grouping
factor. I can analyze the dataset successfully in other software,
including my legacy DOS version BMDP, and R's 'aov' function. I would
like to use 'Anova' in 'car' in order to obtain the sphericity tests
and the H-F corrected p-values. I do not believe the data are truly
deficient in rank. I followed the methods for this kind of analysis
outlined in Bennett's excellent handouts for his Psychology 710 course
http://www.psychology.mcmaster.ca/bennett/psy710/lectures/maxwell_chp12.pdf
I am trying to convert my own similar course to R for my students
for next fall. I have been successful at analyzing a segment of the
data as a 2-way repeated measures design.
Here is my code:
> your.data=read.table(pipe("pbpaste"),header=T)
> your.data
partic A1B1 A1B2 A1B3 A1B4 A2B1 A2B2 A2B3 A2B4 A3B1 A3B2 A3B3 A3B4
1 p1 1 1 2 3 1 2 4 7 1 3 7 10
2 p2 2 2 3 3 2 2 5 6 2 4 6 9
3 p3 1 2 2 3 2 3 2 6 1 4 7 9
4 p4 1 1 2 2 1 2 3 6 2 3 8 10
5 p5 2 2 3 3 2 3 5 7 2 3 7 9
> attach(your.data)
> multmodel=lm(cbind(A1B1, A1B2, A1B3, A1B4, A2B1, A2B2, A2B3, A2B4,
A3B1, A3B2, A3B3, A3B4)~1)
> poke.idata=read.table(pipe("pbpaste"),header=T)
> poke.idata
Afac Bfac
1 A1 B1
2 A1 B2
3 A1 B3
4 A1 B4
5 A2 B1
6 A2 B2
7 A2 B3
8 A2 B4
9 A3 B1
10 A3 B2
11 A3 B3
12 A3 B4
> attach(poke.idata)
>
pokeAnova
=Anova(multmodel,idata=poke.idata,idesign=~Afac*Bfac,type="III")
Error in linear.hypothesis.mlm(mod, hyp.matrix, SSPE = SSPE, idata =
idata, :
The error SSP matrix is apparently of deficient rank = 4 < 6
Thanks for any help or advice. And thanks for the 'car' package, which
is a great asset to my course. I'm just stuck on this one example.
colleen moore
http://www.childrenandpollution.org/ChildrenPollution/ChildrenAndPollution/more_info.html
Colleen F. Moore, Professor
Psychology Department
1202 W. Johnson St.
University of Wisconsin
Madison, WI 53706
cfmo...@wisc.edu
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