Posted by
Maguin, Eugene on
URL: http://spssx-discussion.165.s1.nabble.com/mixed-procedure-question-tp5740325p5740328.html
Hi Bruce,
Thanks for your reply. 0-3 should have been 0-2. The wave*wave term was not-random. It didn't have sufficient variance and stole variance from the linear term. The plot of the data shows that total rises from time=0 to time=1 and rises another small amount at time=2. So you see a quadratic shaped curve. Had wave*wave had variance I would have needed the terms you noted. When I first realized that emmeans required the 'by' word, I made all three variables 'by' variables. Doing so removes the linear assumption and estimates a value at each time point relative the reference for that variable. Perhaps I should have described the problem as a multilevel growth curve model. The log likelihood value for both versions is the same. I got into this problem because I have several significant interactions and I need to look at simple effects. Probably the test command would give me what I need but I've understood how to use it.
Gene Maguin
-----Original Message-----
From: SPSSX(r) Discussion <
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Sent: Thursday, March 18, 2021 6:13 PM
To:
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Subject: Re: mixed procedure question
Hi Gene. If I follow what you're doing, you're missing some terms. If you treated all 3 of your variables as categorical (i.e., had them follow BY), and if you included all 2- and 3-way interactions, you would eat up 11 df (if I counted correctly). So when you treat them as continuous (following WITH), and include polynomial terms where there are 2 or more categories, then you still need 11 df. And I think you are missing a couple of terms.
I reckon you need all of the following terms in your model (with W standing for Wave):
IL
TX
W
W*W
IL*TX
IL*W
IL*W*W
TX*W
TX*W*W
IL*TX*W
IL*TX*W*W
You have only these 8 terms:
wave
wave*wave
tx
wave*tx
il
wave*il
tx*il
wave*tx*il
The 3 you are missing are the ones that involve the quadratic component of the interactions with Wave:
IL*W*W
TX*W*W
IL*TX*W*W
By the way, you said Wave has 3 levels, but then said 0-3. Did you mean 0-2? I assumed you did.
HTH.
Bruce
Maguin, Eugene wrote
> I ran the same multilevel model in mixed two different ways and
> received, no pun, mixed results.
> This is the model statement for way 1. IL and TX are 0,1 variables and
> wave is three time points (0-3)
>
> mixed total with wave tx il/fixed wave wave*wave tx
> wave*tx il wave*il tx*il wave*tx*il/
> print solution/random intercept wave | subject(rid) covtype(un).
>
> Several of the effects are significant and since emmeans doesn't play
> at all with covariates unless a "with" is used, I reversed-coded IL
> and TX and treated them as "by" variables in the way 2 version. When
> ran the model with the reversed variables I was startled to see some
> differences between the two results. The differences were in the Type
> III Tests of Fixed Effect table. Of the nine terms, including the
> intercept, six are different between the two model versions. Different
> in the denominator dof, F value, and significance values. But when I
> look at the Estimates of Fixed effects table: no differences, the same
> estimates, SEs, dfs, etc for both models. The same is true of the
> covariance parameters. Furthermore, the significance values in the
> Type III table and Estimates table correspond in the way 1 model but
> not so for the way 2 model using the reversed items and the "by" keyword.
>
> I can't make up plausible story for these differences. Can someone
> help me?
> Thanks, Gene Maguin
>
>
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