Hi
> On Fri, 29 Sep 2000, Lu=EDs Silva wrote:
> > For a certain variable I applied a Three Factor ANOVA and found a
> > significant interaction between two factors.=20
> > I have two levels for each factor. Then, I applied the HSD Tukey test=
=20
> > for multiple unplanned comparisons, in order to detect what are the=20
> > significantly different treatments.
Given an interaction, the comparisons that generally are of most
interest are the simple effects; that is, the effects of one
factor at each level of the other. With four conditions defined
by two levels each of A and B, one would have A1B1, A1B2, A2B1,
and A2B2. The possible simple effects are A1B1 vs A1B2 and A2B1
vs A2B2 OR A1B1 vs A2B1 and A1B2 vs A2B2. Normally you would
choose one of these two sets (i.e., simple effects of B within A1
and A2 or simple effects of A within B1 and B2).
You probably have some flexibility as to whether you use some
correction (e.g., Tukey's), depending on whether the pattern was
expected, how strong the different simple effects are, and so on. =20
One "ideal" outcome is for one simple effect (e.g., A1 vs A2 at
B1) to be not at all significant (no matter how liberal the
test), and the other to be clearly significant (e.g., A1 vs A2 at
B2) (no matter how conservative the test).
Best wishes
Jim
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James M. Clark=09=09=09=09(204) 786-9757
Department of Psychology=09=09(204) 774-4134 Fax
University of Winnipeg=09=09=094L05D
Winnipeg, Manitoba R3B [EMAIL PROTECTED]
CANADA=09=09=09=09=09http://www.uwinnipeg.ca/~clark
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