[R-sig-ME] Theta Value in glmer

[Ben Bolker]

    I also don't really know what's going on here.

Some thoughts:

    * for NB fits, glmmTMB, which is a bit faster & more stable than 
glmer for this special case (and is pretty nearly a drop-in replacement 
for glmer.nb)
    * A common case of convergence problems for NB models is when you 
try to fit data that are equi-dispersed or underdispersed (conditional 
variance <= mean rather than >mean), in which case the theta coefficient 
gets very large (and the likelihood surface gets very flat).  In this 
case you're better of with a Poisson model anyway ...
    * Not sure what you mean by "the vignette of glmer" - there isn't 
any vignette describing glmer in the lme4 package AFAIK ...

On 8/3/21 4:39 PM, Phillip Alday wrote:
> Hi Amir,
> 
> can you share an anonymized version of your data? Or give a bit more of
> a minimal working example (MWE)? Then we can probably provide more and
> better help. :)
> 
> Best,
> Phillip
> 
> On 17/07/2021 01:22, Amirhossein.AmirhosseinTalebi using radboudumc.nl wrote:
>> Dear all,
>>
>> I am trying to fit a negative binomial regression using lme4 package. After several attempts using glmer.nb and having error of convergence, I have switched to glmer function to could set the argument nAGQ=0 and used negative binomial function as the family argument.
>> The question here is, as the theta value in negative binomial function I tried to use the theta value that glm.nb of package MASS gave me (157); but based on the vignette of glmer I can use theta=1.75. Could you please clarify that how can I choose the best theta value here and until what extend that can change my results? Or based on what parameter in model output I can understand that I used the best theta value?
>>
>> Kind regards,
>> Amir
>>
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-- 
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
Graduate chair, Mathematics & Statistics