[R-sig-ME] R-sig-mixed-models Digest, Vol 176, Issue 4

Amirhossei@@Amirhossei@T@iebi m@iii@g oii r@dboudumc@@i Amirhossei@@Amirhossei@T@iebi m@iii@g oii r@dboudumc@@i
Fri Aug 20 17:14:03 CEST 2021 

Dear Philip , Thierry, Ben and other list followers,

Thanks for your response.
Maybe the following codes can help you get a feel of the data that I am using, due to working in a cloud server I cannot share the real data I use. I also shared the latest models formula I tried to run but every time I have convergence problems :-(

set.seed(1)
df<-data.frame(id=rep(1:3,each=4),treatment=sample(c(0,1),12,replace = T),
               event=sample(c(0,1),12,replace = T),
               person.time=sample(c(15,31,30),12,replace = T),
               age=rep(c(65,58,74),each=4),gender=rep(c("m","f","m"),each=4))
df$person.time<-ave(df$person.time,df$id,FUN = cumsum)
df$logtime<-log(df$person.time)
# codes for model:
library(lme4)
nbm<-glmer.nb(event~treatment+age+gender+offset(logtime)+(1|id),df,glmerControl(optCtrl = list(maxfun=50)),verbose = T)
#END.


Please note that in data an individual can have multiple events over time and the treatment is a time variant variable; in real data I do not have complete separation problem.

Bests, Amir

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Subject: R-sig-mixed-models Digest, Vol 176, Issue 4

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Today's Topics:

   1. Re: Theta Value in glmer (Ben Bolker)

----------------------------------------------------------------------

Message: 1
Date: Tue, 3 Aug 2021 18:23:20 -0400
From: Ben Bolker <bbolker using gmail.com>
To: r-sig-mixed-models using r-project.org
Subject: Re: [R-sig-ME] Theta Value in glmer
Message-ID: <cc456f6e-32b1-6a0a-dc98-91e9423fd11a using gmail.com>
Content-Type: text/plain; charset="utf-8"; Format="flowed"

    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




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