[R-sig-ME] Most principled reporting of mixed-effect model regression coefficients

Ades, James j@de@ @end|ng |rom he@|th@uc@d@edu
Fri Feb 14 08:59:34 CET 2020

Hi all,

It�s been surprisingly difficult to find the most principled reporting of mixed-effect model regression coefficients (for individual fixed-effects). One stack overflow article lead me to this paper�a systematic review of the incorporating and reporting of GLMMs ( https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112653#pone.0112653.s001)  which references a paper by Ben Bolker (https://www.sciencedirect.com/science/article/pii/S0169534709000196). Oddly, I don�t really find an answer to this in either of those. I�ve heard mixed things regarding fixed effect coefficients in LMM (that LMM/and GLMMs are more about the predictive power of an entire model than the individual predictors themselves), but overall, my understanding is that it�s kosher (and informative) to look at effect sizes of regression (fixed effect) coefficients�only that lme4 doesn�t currently provide p values (though Lmertest does).

It seems like reporting effect size of regression coefficients and their SEs should suffice; though sometimes people report CI with those as well (but isn�t that a little redundant). My PI is telling me to include p-values. So many different things, so little agreement.

I figured I�d turn here for something of a �definitive� answer.

Ben, I definitely need to go back and read through your paper more thoroughly for a deeper understanding of the nuances of GLMMs. Currently watching�and reading�McElreath�s Statistical Rethinking, but I�m not quite at the level of implementing MCMCs.

Much thanks,


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