Date: Wed, 21 May 2008 11:00:07 -0500
Reply-To: "Swank, Paul R" <Paul.R.Swank@uth.tmc.edu>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: "Swank, Paul R" <Paul.R.Swank@uth.tmc.edu>
Subject: Re: comparing groups before and after treatment
In-Reply-To: <007901c8bad1$1b277100$c0f4fea9@abhome>
Content-Type: text/plain; charset="us-ascii"
Two points. First, a multivariate test would be appropriate if there is
a strong relation among the measured variables but you need to be
prepared to interpret a composite. Secondly, while this test will tell
you whether or not there was significant change over time, it cannot
tell you it was due to what you did. Without random assignment to
treatment or control conditions, you cannot infer causality.
Paul R. Swank, Ph.D.
Professor and Director of Research
Children's Learning Institute
University of Texas Health Science Center - Houston
-----Original Message-----
From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of
Angshu Bhowmik
Sent: Tuesday, May 20, 2008 6:28 PM
To: SPSSX-L@LISTSERV.UGA.EDU
Subject: comparing groups before and after treatment
Hello everyone,
I wonder if anyone could advise me (a clinical doctor with no
statistical
training) about the correct way to test whether people have improved in
8
variables (e.g. how far they can walk, blood oxygen levels, spirometry,
etc)
after an exercise program. I think they have, and the patients love it,
but
I need to formally confirm it in order to keep the service running.
If I understand correctly, simply doing paired t-tests or Wilcoxon's
tests
on each variable is not correct because multiple comparisons make it
more
likely that something will show up. Is doing multiple t-tests and
changing
the desired p value to 0.05 / 8 i.e. 0.00625 the only way to do this?
Many thanks for your kind help
Angshu
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