Hi
On 17 Feb 2004, Donald Burrill wrote:
> (One could have constructed <d*g> to be orthogonal to both <d> and <g>
> -- see my White Paper on interactions in MR, on the MINITAB web site
> www.minitab.com for an example and description of how to do that -- so
> that <d*g> represents what one might call the "pure interaction" effect,
> uncontaminated with main effects; for this variable in Karl's example,
> used as a predictor all by itself (in MR, not ANOVA), the SS would be
> rather more like 15.9 than 1312.3.)
>
> On Mon, 16 Feb 2004, Karl L. Wuensch wrote:
>
> > Here is SAS GLM output for a 2x2 ANOVA, unequal cell sizes, type
> > III sums of squares. First the full factorial design:
> > Source DF Type III SS
> > deattr 1 1286.325649
> > gender 1 3.955131
> > deattr*gender 1 15.873457
> >
> > Now I drop the two main effects and run the analysis again:
> > Source DF Type III SS
> > deattr*gender 3 1312.292621
> >
> > As you can, both the sums of squares and the df previously assigned
> > to the main effects are now assigned to the interaction term.
If one specifies an interaction-only model in SPSS (at least for
equal n design), then the SS and df for the interaction remain
the same. The excluded dfs and SSs go to the error. Using
MANOVA, this would involve contrasting:
full factorial: MANOVA y BY a b /DESIGN
and
interaction: MANOVA y BY a b /DESIGN a BY b
Perhaps one situation where it might be desirable to conduct this
interaction-only analysis is with very few df for the default
error and very small SS for the main effects? But under most
circumstances I can imagine, it does seem unusual to risk
contaminating either the numerator or denominator (or both?) of
the F for the interaction effect.
Best wishes
Jim
============================================================================
James M. Clark (204) 786-9757
Department of Psychology (204) 774-4134 Fax
University of Winnipeg 4L05D
Winnipeg, Manitoba R3B 2E9 [EMAIL PROTECTED]
CANADA http://www.uwinnipeg.ca/~clark
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