Hi
On 3 Dec 2003, Karl wrote:
> Hallo!
>
> I have data of the following design:
> N subjects were measured at Baseline (visit 1) and at 3 following time
> points (visit 2-4). There is or is not a treatment. Say, the results
> of visits 1 to 4 are Y1, Y2, Y3, Y4.
>
> T: Variable Treatment (yes/no)
> V: Variable Visit (2, 3, 4 - without baseline)
> id: Variable subject identification number
> N: number of subjects
>
> Most interesting is the question if there is a difference in treatment
> between the results of visit 4 and baseline. (The other time points
> are also of interest.)
>
> I am thinking of different possibilities for the analysis (balanced
> design):
Perhaps straight factorial anova with contrasts, followed by
simple effects within treatment? In SPSS MANOVA terms:
MANOVA y1 y2 y3 y4 BY t(1 2) /WSF = time(4)
/CONTRAST(time) = SPECIAL( 1 1 1 1
-3 1 1 1
0 -1 0 +1
0 -1 +2 -1)
/WSD /DESIGN
/WSD time /DESIGN MWITHIN t(1) MWITHIN t(2)
First analysis will give main effects of treatment, time, and
interaction, along with partition of time and timextreatment into
3 single df contrasts. Contrast 1 is y1 vs. y2-y4, second is
linear effect of y2-y4, and third is quadratic effect of
y2-y4. Selection of contrasts depends on what pattern you expect
across times.
Second analysis will report simple effects of time within control
and treatment conditions, again partitioned into single df
effects specified in contrast statement.
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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