[R-sig-ME] Modeling and Interpretation Question for Interaction in LMER Output.

[Ades, James]

Hi all,

I looked through several different nlme sources and this is what seemed to be the equivalent model using corCAR1(). I have two questions: is it legitimate to put timepoint (character, 4 "levels") as a fixed effect while keeping t4 (time, numeric, days from first testing point) as the random slope, so that I can have a more interpretable outcome to assess the effects of time per cohort with emmeans? 2) As you can see in the lmer() model, there are random effects of pid as well as an interaction between pid:task; however, what I've coded above seemed to be the equivalent in nlme. Is that accurate, or is there a different way of coding that interaction?

lme(level ~ task + timepoint * cohort,
    random = list(pid = ~t4, task = ~t4),
    correlation = corCAR1(),
    dat)


lmer(level ~ task + t4 * cohort + (t4|pid) + (t4|pid:task))

Thanks!

James


________________________________
From: David Duffy <David.Duffy using qimrberghofer.edu.au>
Sent: Thursday, June 11, 2020 7:53 PM
To: Ades, James <jades using health.ucsd.edu>; r-sig-mixed-models using r-project.org <r-sig-mixed-models using r-project.org>
Subject: Re: Modeling and Interpretation Question for Interaction in LMER Output.

> The modeling question regards my depiction of time. The amount of elapsed time
> between participants and testing points is not equal equal. Students in the same classroom
> will be measured at equal time points, but while one class might have 4 months
> in between testing, another class might have 7 months.

In lme, AIUI this would be comparing different correlation structures, as per the example for
corCAR1().

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