[R-sig-ME] About modelling time as continuous variable in a glmmTMB-based model.

Julian Gaviria Lopez Ju||@n@G@v|r|@Lopez @end|ng |rom un|ge@ch
Tue Jul 16 17:25:58 CEST 2019

Dear lists members,

Based on the glmmTMB-based model:

Model 1. Time as a fixed factor:
zipoisson <- glmmTMB(Observations ~ CAP * Time + (1|ID), data=mDATA, ziformula=~ CAP * Time , family=poisson)

A gentle member from this list suggested me to treat time as continuous.  Since I am new with mixed models, I would like to confirm that the new models for this aim are right:

Model 2. Time as continuous variable:
zipoisson <- glmmTMB(Observations ~ CAP * Time + (ID|Time), data=mDATA, ziformula=~ CAP * Time, family=poisson)

Model 3.  Time as continuous, with the dispersion parameter identical for each observation:
zipoisson <- glmmTMB(Observations ~ CAP + (ID|Time), data=mDATA, ziformula=~ 1, family=poisson)

It calls my attention that models 1 and 2 yield the same results. In this way, I wonder whether I did model time properly. Maybe I should introduce the levels of "Time" differently?

current arranging of time data:

Alternative option?

I thank you in advance for any comment in this regard.

Best regards,

Julian Gaviria
Neurology and Imaging of cognition lab (Labnic)
University of Geneva. Campus Biotech.
9 Chemin des Mines, 1202 Geneva, CH
Tel: +41 22 379 0380
Email: Julian.GaviriaLopez using unige.ch

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