Re: Interpretation of interaction with time-varying predictor (Growth model)

Posted by Bruce Weaver on Mar 16, 2021; 8:52pm
URL: http://spssx-discussion.165.s1.nabble.com/Interpretation-of-interaction-with-time-varying-predictor-Growth-model-tp5740294p5740317.html

This example is from the MIXED - EMMEANS documentation:

MIXED Y BY A B WITH X
  /FIXED A B X
  /EMMEANS TABLES(A*B) WITH(X=0.23) COMPARE(A) ADJ(SIDAK)
  /EMMEANS TABLES(A*B) WITH(X=MEAN) COMPARE(A) REFCAT(LAST) ADJ(LSD).

Notice the use of WITH(X=Value) to examine the A*B interaction with X set to
some desired value.  In your model, Time is the lone categorical variable,
so the EMMEANS sub-commands will look more like this:

  /EMMEANS TABLES(Time) WITH(Dep=a) COMPARE(Time) ADJ(SIDAK)
  /EMMEANS TABLES(Time) WITH(Dep=b) COMPARE(Time) ADJ(SIDAK)
  /EMMEANS TABLES(Time) WITH(Dep=c) COMPARE(Time) ADJ(SIDAK)

Replace a, b and c with low, medium and high values of Dep to inspect the
simple effects of Time at those values of Dep.  And if you want to look at
more than 3 values of Dep, go ahead.  

I'm not convinced that the COMPARE(TIME) part of those lines is needed,
given that you have Time as the only categorical variable.  You could try
with and without to see which one works, or whether they give the same
results if both work.  

HTH.  



Oliver wrote

> Rich & Bruce,
>
> Thanks for your very useful input. This is much appreciated !
>
> As suggested, I've coded "Time" as a categorical variable using "BY", and
> results revealed a significant main effect of Time (p = .000). I've then
> used the /TEST subcommand to perform planned contrasts to help data
> interpretation of the "Time" effect on pain. Assuming that I did it
> correclty, I conducted the Helmert contrast, as suggested by Bruce (i.e.,
> comparing pain at each time point versus the mean of all other subsequent
> time points.
>
> MIXED Pain BY Time
> /METHOD = REML
> /PRINT = SOLUTION TESTCOV
> /FIXED =
> Time
> | SSTYP(3)
> /RANDOM = INTERCEPT | SUBJECT(ID) COVTYPE(UN)
> /REPEATED = Wave | SUBJECT(ID) COVTYPE(AR1)
> /EMMEANS = TABLES(Time)
> /TEST = "Planned contrasts of TimeBaseline versus subsequent" time  1 -1/4
> -1/4 -1/4 -1/4
> /TEST = "Planned contrasts of 3m versus subsequent" time  0 1 -1/3 -1/3
> -1/3
> /TEST = "Planned contrasts of 6m versus subsequent" time  0 0 1 -1/2 -1/2
> /TEST = "Planned contrasts of 9m versus subsequent" time  0 0 0 1 -1
>
>
> *At this point what I'm wondering is how to interpret the Time *
> Depression
> (Dep) interaction effect. When coding "Time" as categorical, the
> interaction effect (i.e., Time * Dep) is significant. But I don't know how
> to use planned contrasts to probe the interaction effect. For instance, it
> is possible that depression scores (continuous: 0-10) influenced pain
> (continous: 0-10) but only between the baseline and the 3 month follow-up
> time point. I read on the UCLA website that "*interaction contrasts*"
> could
> be used
> (https://stats.idre.ucla.edu/spss/faq/how-can-i-test-contrasts-and-interaction-contrasts-in-a-mixed-model/),
> but for some reason I can't figure out how to apply the coding to my Time
> *
> Dep interaction.
>
> MIXED Pain BY Time WITH Dep
> /METHOD = REML
> /PRINT = SOLUTION TESTCOV
> /FIXED = Time Dep Time * Dep
> | SSTYP(3)
> /RANDOM = INTERCEPT | SUBJECT(ID) COVTYPE(UN)
> /REPEATED = Wave | SUBJECT(ID) COVTYPE(AR1)
>
> By any chance, does someone here know how to perform the "interaction
> contrasts" ? Any assistance would be tremendously appreciated, as usual.
> O.
>
>
>
>
>
>
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