Date: Thu, 1 Apr 1999 14:33:10 -0500
Reply-To: Lary Jones <ljones@BINGHAMTON.EDU>
Sender: "SPSSX(r) Discussion" <SPSSX-L@UGA.CC.UGA.EDU>
From: Lary Jones <ljones@BINGHAMTON.EDU>
Subject: Appropriate design: measures of factor
Content-Type: text/plain; charset="us-ascii"
Statis-tickle wizards:
I really did not get a lot of feed back on the following. Let me
re-present this with a bit more detail. I was trying to protect the
content of the research, but I may not have provided enough detail for you
to respond appropriately.
~~~~~~~~~~~~~~
A PhD student in psychology came to me with a question about how to
impliment a design in GLM. This question is really about choices in the
design, not so much a question of software options. For purposes of this
question let's say that there are:
Between Groups Factors:
Gender
"Treatment"
Within Subjects
5 (pseudo?) clinical sessions or trials
During each one of the sesions/trials the subjects refers to a number of
past events. Upon checking (with permission) some of these are verified to
occur and some are not verified.
Each of the subjects returns 4 times and similar classifications and counts
occur in connection with each session. The dependent measures at each
"trial" are the number of verified memories and the number of unverified
memories, such as 10 verified and 7 unverified out of 17 (the number of
events referred to in a session is toally free; it could be 1 or 5 or 17 or
50, for that matter).
It is unclear to me whether it is better to make this another W/S factor
(verified/unverified), or treat these as multivariate "measures" taken at
each trial. Making this a factor does allow for the direct testing of
interactions with other factors. Treating this as "measures" means one
would look at the discriminant function of the measures for interpretation.
One could record this as the % of verified memories (and do the arcsin
transformation), but this would lose the number of memories/events brought
up, which i think is important.
Which way would you go?
Thanks again,
Lary Jones
_______________________________________________________
Lary Jones % Statistical Computing Analyst
Computing Services % ..........................
Binghamton University % LJones@Binghamton.EDU
Binghamton, NY 13902-6000 % (607) 777-2879
