R help - Feb 2021 - time as a continuous factor in a linear mixed effects model

Hello,

I am interested in investigating the main effects of group, time, and group
by time interaction on survey outcomes using linear mixed effects models.
Time is considered as continuous (number of days since baseline), but isn't
it also categorical, since I want to compare Session 1 vs Session 4 (for
example)? How is that handled in the model? As of now, time (days since
baseline) is being treated as one unit, rather than four separate sessions.

Here is an example of my code: mdl.outcome <- lmer(outcome ~ time*Group +
(1 | PID), data = dta)

Thank you!!
laura

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You should post this on the r-sig-mixed-models list rather than here.


Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Thu, Feb 25, 2021 at 9:20 AM Laura Coco <lauracoco at gmail.com> wrote:
> Hello,
>
> I am interested in investigating the main effects of group, time, and group
> by time interaction on survey outcomes using linear mixed effects models.
> Time is considered as continuous (number of days since baseline), but
isn't
> it also categorical, since I want to compare Session 1 vs Session 4 (for
> example)? How is that handled in the model? As of now, time (days since
> baseline) is being treated as one unit, rather than four separate sessions.
>
> Here is an example of my code: mdl.outcome <- lmer(outcome ~ time*Group
+
> (1 | PID), data = dta)
>
> Thank you!!
> laura
>
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>
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