I am familiar with two ways of analyzing repeated measures effects in
jmp. One of them uses a vertically-organized file structure, with
multiple lines per subject, and uses subject as a random factor. The
other uses a horizontally-organized file structure, with MANOVA. (Fit
Model: MANOVA Personality: Choose Response: Coompound; interaction
effects) The former approach makes sense to me and I can get it to
work. However, I have the same dataset organized both ways, and I
cannot get the MANOVA approach to reproduce the results I obtain in
the random effects approach. Maybe it's not supposed to? And I don't
know MANOVA, so maybe I'm not looking in the right way. If anyone is
sufficiently interested and knowledgeable, I'd appreciate your input.
I'm attaching the two datasets in case you want to check 'em out.
In the horizontal file, the four variables, prefleft, prefright,
nonleft, nonright represent the repeated measures. The two within-
subjects variables are laterality (left versus right) and preference
(pref versus nonpref). So laterality is the faster moving variable.
Orientation is a between-subjects factor. As an example of a result I
would like to find in the MANOVA, in the random effects analysis
(with all main effects and interactions), I get a significant
interaction for Prefnon*Orientation, F(1,59)=10.8, P=.0017.
amygdalahorizontal.jmp
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amygdalahorizontal.jmp
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amygdalavertical.jmp
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amygdalavertical.jmp
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Michael Bailey
jm-bailey@northwestern.edu
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