[R-sig-ME] Choice of distribution for random effects

Andrew Robinson @pro @end|ng |rom un|me|b@edu@@u
Wed Jul 20 09:40:17 CEST 2022

You can use a qq-plot of the BLUPS to guide that decision.

The difference might also be due to something else, though.  Have you tried the call to hglm2 with a gaussian random effects family?  Does it give the same output as the glmer?

For: does the choice of distribution for the fixed effects portion of the model inform the choice for the random effects?  I’m not sure what you mean - do you mean the exponential family for the response variable?



Andrew Robinson
Chief Executive Officer, CEBRA and Professor of Biosecurity,
School/s of BioSciences and Mathematics & Statistics
University of Melbourne, VIC 3010 Australia
Tel: (+61) 0403 138 955
Email: apro using unimelb.edu.au
Website: https://researchers.ms.unimelb.edu.au/~apro@unimelb/

I acknowledge the Traditional Owners of the land I inhabit, and pay my respects to their Elders.
On 20 Jul 2022, 2:27 PM +1000, J.D. Haltigan <jhaltiga using gmail.com>, wrote:

Is there clear best practice or guidance when it comes to choosing the
distribution of random effects where multiple choices exist (e.g.,
gaussian, gamma, etc.)? I ask in the context of extending some analyses
from an RCT in which the outcome is symptomatic seropositivity (so a
count). The random effects I am modeling are village cluster [union] (it's
a cluster randomized trial). I get different results (significance-wise)
depending on whether I choose a normal or gamma distribution for the random

The basic model (proportional outcome) is:

lme4_5_B = glmer(posXsymp~ treatment+proper_mask_base+prop_resp_ill_base_2
+ pairID + (1 | union), family = "poisson", nAGQ=0, data = bdata.raw3)#lme4
package using glmer

HGLM2_5_A = hglm2(posXsymp~ treatment+proper_mask_base+prop_resp_ill_base_2
+ pairID + (1 | union), family =poisson (link = log), rand.family
data = bdata.raw3)#HGLM package using hglm2

Does, for example, the choice of distribution for the fixed effects portion
of the model inform the choice for the random effects?

Thank you for any insights.

Best regards,

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