Posted by
Maguin, Eugene on
Nov 24, 2014; 4:45pm
URL: http://spssx-discussion.165.s1.nabble.com/REPEATED-MIXED-MODELS-post-hoc-tests-contrasts-tp5728007p5728013.html
I'm assuming that LMM means the Mixed command. I urge you to look in the Syntax Reference at Models 9 and 10 in the examples for Mixed. It's time to learn and use syntax. You don't say but if you measured anxiety once, i.e., trait anxiety, then Model 9 is a good example. If you measured anxiety, i.e., state anxiety, prior to each presentation, then Model 10 is a good example because anxiety is a time varying covariate.
With respect to the random intercept, I want to defer to others who are more experienced.
That you have that anxiety covariate and are looking for a list-length by anxiety interaction is complicated. Perhaps you've done this already but I suggest plotting the DV by anxiety by list length to get an idea of where the interactions may exist. You also ought to save and plot the fixed predicted values (assuming no random effects) by anxiety and list length (and for the same reason). If there is an interaction, you need to identify what is called, I believe, "regions of significance". At least one person has written a macro for this and I don't recall who it is. I believe that you can iteratively identify the region boundaries using emmeans because you can iterate on covariate (i.e., anxiety) values and see the significance of the difference. The Test subcommand is more powerful but harder to use.
Gene Maguin
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of Alexandra
Sent: Monday, November 24, 2014 11:02 AM
To:
[hidden email]
Subject: REPEATED MIXED MODELS-post hoc tests/contrasts
Hello!
I am studying the effect of trait anxiety on working memory efficiency
(RT) and accuracy and I need some help with using LMM.
The working memory task had four blocks varying in list length presentation, presented to each subject (1,2,3,4 words to recall). I was thinking to run a LMM with a random intercept with RT / ACC as a DV, list length as a repeated within factor (or covariate?), anxiety as a covariate.
Therefore, I have the fixed effects: list length, anxiety and list length * anxiety interaction and at random effects, include intercept and Subjects (is that ok?)
So I have the following variables:
DV: efficiency score/ accuracy for every list length (continuous-within repeated measure)
IV: list length (categorical)
Covariate: trait anxiety (continuous)
*each repeated measure (level 1) is within subject category (level 2). I already put the data in long format.
My questions are:
1) in order for SPSS to know it's repeated data, should I choose from the
first window of LMM, Subject ID at subjects and list length as a repeated measure? Or is it enough subjects and then include the random intercept?
2) * how do I compare between list lengths? I want to show for example that list length’s effect is more significant at list length 4 that list length 1. So there are sign differences between lists. Should I use post hoc tests?
Also, how do I compare which list length is more affected by it’s interaction with anxiety? Is there a contrast option in LMM for that?*
Thanks a lot! any kind of input would be very very helpful...
Alexandra
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