|Date: ||Fri, 17 Nov 2006 22:20:33 -0500|
|Reply-To: ||Statisticsdoc <firstname.lastname@example.org>|
|Sender: ||"SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>|
|From: ||Statisticsdoc <email@example.com>|
|Subject: ||Re: your assistance, please|
|Content-Type: ||text/plain; charset="us-ascii"|
Your design appears to be a Repeated Measures ANOVA, with three levels of
the between-subject factor (C+I, I only, No Treatment) and two levels of the
within-subject time factor. It would have concerns about letting subjects
self-select into the static control group. If you can, you want to start
with a group of subjects who are willing to participate in the treatments
and randomly assign some to a static control group (perhaps a waiting list
control group, if the treatment is something of benefit to the
participants). Letting subjects self-select out of the treatments means
that the groups do not consist of comparable groups of randomly selected
individuals. The inferences that you can draw are weaker: to what extent
does the control group differ because of treatment effects or
For personalized and professional consultation in statistics and research
From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU]On Behalf Of
Sent: Friday, November 17, 2006 8:39 PM
Subject: your assistance, please
To the experts,
To determine differences between conditions such as the following, what
would be most appropriate -
The 2 conditions for the I.V. are (C+I) and (I only) with pre and post
tests. If some subjects who are giving the pretest
decide not to participate in condition 1 or 2, I would like to put them
into a static or control group.
Would it be appropriate to use a Repeat Measures Mixed ANOVA procedure?
One I.V. is (C+I) and (I only) and the second I.V. is the time - i.e.
from pre to post?
Would the same statistical method be appropriate if I randomly assign
the 3 conditions
(C+I) and (I only) and (control/static) conditions to a specific
Thank you so much for your assistance,
Helga S. Walz, Ph.D.
Division of Applied Behavioral Sciences
University of Baltimore
1420 North Charles Street
Baltimore, Maryland 21201
Tel.: 410 837-5279