On 8 Dec 2003 11:09:20 -0800, [EMAIL PROTECTED] (Frank Rigous)
wrote:
> 
> I am new to the group and not very experienced in statistics. I
> thought I had a classical design, two groups with either treatment A
> or B, measuring the response at 4 time point where the first one is a
> baseline measurement. I was very astonished not finding any example
> for this design.

Randomized, I hope.

That sounds classical enough, if you expect a linear trend
and that is what you will test for.  Look for "trend".

> 
> My first idea of analysing was to calculate 3 t-tests with the
> difference to baseline. But as I found (e.g. Altmann) this is not
> recommended. He suggested a summary statistic - but this seems not
> possible because the course in time may vary a lot.

*How*  might the course in time vary?

If the advantage is early and sustained, then you get a
powerful test by using the average of the three as 'outcome'.
Usually, the best test of 'final outcome'  (the way that you might
describe this one)  will be the one-way analysis of covariance.
That  compares the regressed-change scores.

If the advantage is slow and late, you might get the effective 
test by ignoring time2 and time3 -- just test time4 with base-
covariate, instead of taking an average of 2, 3, and 4.

I set up a design for some drug studies where the initial impact
was *strong*  and was followed by several periods of 
(a) no-more-change,  (b) further drift in the same direction, or 
(c) drift back towards baseline.  That would have been tougher
to test against placebo, but those were big changes and we
were satisfied to describe them:  as size of change, and the
subsequent  linear trend.

[ snip, items not especially  relevant now]

-- 
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
"Taxes are the price we pay for civilization." 
.
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