http://spssx-discussion.165.s1.nabble.com/Linear-Mixed-Model-in-SPSS-Guidance-tp5737698p5737721.html
It isn’t clear to me why the reviewer feels so strongly about an LMM in this particular circumstance.
I would expect the fixed effects results from a repeated measures ANOVA and LMM using data from a fully balanced 2 group-by-2 time point design [with no missing data] to be identical.
> On Apr 23, 2019, at 4:32 PM, Maguin, Eugene <
[hidden email]> wrote:
>
> I agree. Multilevel is overkill but then there is this sentence in Martin's reply to me, " 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)."
> Gene Maguin
>
>
> -----Original Message-----
> From: SPSSX(r) Discussion <
[hidden email]> On Behalf Of Bruce Weaver
> Sent: Tuesday, April 23, 2019 5:23 PM
> To:
[hidden email]
> Subject: Re: Linear Mixed Model in SPSS Guidance
>
> I agree with David. Multilevel modeling would seem like overkill with only 2 repeated measures. Here's a short BMJ Statistics Note you may find helpful, Martin.
>
>
https://www.bmj.com/content/323/7321/1123.full>
> Cheers,
> Bruce
>
>
> David Greenberg wrote
>> No need for multilevel modeling here. Your data do not violate the
>> assumption of independence of observations. David Greenberg
>>
>> On Tue, Apr 23, 2019 at 9:00 AM Martin Sherman <
>
>> MSherman@
>
>> > wrote:
>>>
>>> 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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> -----
> --
> Bruce Weaver
>
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