[R-sig-ME] About computing pairwise associations (corr) of random effects in glmms

[Julian Gaviria Lopez]

Dear Dr. Kristensen,


I aim to assess the association of the random effects computed by a glmm. I wondered whether it was possible to carry out the analysis with the glmmTMB package, then I found your vignet about the Covariance structures with glmmTMB. I know it is about the covariances that complete the model specification, therefore it is unrelated to my analysis. Nevertheless, I wonder whether you could suggest me one way to accomplish my goal:


I have nested data comprised by 2 factors (conditions: A and B). Each factor has 8 levels: (clusters: c1,c2,c3,c4,c5,c6,c7,c8). N=33. Aim: To assess the pairwise association between the factors Then, the syntax of the model would be as follows:


gmodel <- glmmTMB(observation ~ condition  + cluster (1|subject), data=mDATA, family=poisson)

Then I wonder how I could extract the pairwise correlation of the fixed effects (i.e. correlation between Ac1 and   Bc1, etc.). Is it feasible to run the analysis with glmmmTMB?

Thanks in advance for any comment on this regard.


P.d. sorry for any multiple posting. I sent this question to the r-sig-mixed-models list as well.

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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