I suggest that you look at Singer and Willett’s book Applied Longitudinal Data Analysis. It’s not an spss-based book, so you won’t get spss command language examples
but I do think that you will get a good introduction to working through the model building process. Given where you seem to be at this will help with whatever you do next.
Gene Maguin
From: Martin Sherman <[hidden email]>
Sent: Tuesday, April 23, 2019 11:08 AM
To: Maguin, Eugene <[hidden email]>
Subject: RE: Linear Mixed Model in SPSS Guidance
The editor at the International Journal of Eating Disorders stated that the journal does not approve of repeated measures ANOVA and requires a Hierarchical Linear Modeling
or Mixed Linear Modeling or MANOVA (which is least preferred). The only significant effect that I found with repeated measures was a pre post time effect (ns are large with 100 per treatment condition). The results will not be different regardless of which
procedure I use but the journal will not accept the repeated measures anova. I just want to make sure I know what I am doing and it is correct. The book on Linear Mixed Models is way over my level of comprehension. Thus, I look for examples that come close
to what I need to do. martin
From: Maguin, Eugene <[hidden email]>
Sent: Tuesday, April 23, 2019 10:46 AM
To: Martin Sherman <[hidden email]>;
[hidden email]
Subject: RE: Linear Mixed Model in SPSS Guidance
It seems that your decision to use a mixed model is pushed by the pre-post correlations. What is it about those correlations that recommend a mixed model over
repeated measures?
Gene Maguin
From: SPSSX(r) Discussion <[hidden email]>
On Behalf Of Martin Sherman
Sent: Tuesday, April 23, 2019 9:00 AM
To: [hidden email]
Subject: Linear Mixed Model in SPSS Guidance
Dear List: I am working on pretest/post-test study with two between group factors, Treatment (Therapy A vs. Therapy B) and Age (younger vs. Older) on various outcome variables
(all continuous). I originally considered doing a repeated measures analysis but after reading up on the pros and cons of such an analysis I decided that a linear mixed model would be more appropriate given the correlation between the pre-test scores and
the post-test scores. To further my understanding I reviewed the text by Verbeke and Molenberghs (Linear Mixed Models for Longitudinal Data). Getting through the text proved to be a challenge (many many equations beyond my pay grade). So I starting looking
for some dummy downed explanations on how to set up my statistical model. So far that have not generated any comparable examples of my design (2 x 2 x (2)). I am hoping there are some folks on the listserve that might be able to point me in some directions
that will prove to be beneficial. I have googled but I have not found any helpful tutorials. Per chance if anyone has a good tutorial for my design I would appreciate hearing from you. Thanks, martin sherman
Martin F. Sherman, Ph.D.
Professor of Psychology
Loyola University Maryland
4501 North Charles Street
222 B Beatty Hall
Baltimore, MD 21210
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