[R-sig-ME] Time-dependent Negative binomial regression

[Ben Bolker]

   I think log(person.time) will actually work fine, although I() 
doesn't hurt (it's only transformations that involve operators that are 
also used by R's formula syntax (*, +, :, /, ^) that need to be 
protected by I().



On 7/8/21 5:06 AM, Thierry Onkelinx via R-sig-mixed-models wrote:
> Dear Amir,
> 
> Have a look at the lme4, glmmTMB or INLA packages. Note that if you need on
> the fly transformations in the model you need to code them as
> I(log(person.time)) instead of log(person.time). Personally, I prefer to
> create a new variable in the data.frame and use that new variable in the
> model.
> 
> Another thing is that you shouldn't use gender and baseline.age as random
> effects. Either don't use them (as their effect is handled by the id random
> effect) or add them as fixed effects.
> 
> library(lme4)
> glmer.nb(event ~ offset(log_time) + treatment + gender + baseline.age +
> (1|id), data = df)
> 
> Best regards,
> 
> 
> ir. Thierry Onkelinx
> Statisticus / Statistician
> 
> Vlaamse Overheid / Government of Flanders
> INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
> FOREST
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> 
> Op do 8 jul. 2021 om 08:59 schreef <
> Amirhossein.AmirhosseinTalebi using radboudumc.nl>:
> 
>> Dear responders,
>>
>>
>> Recently I have processed and cleaned a data for the aim of application of
>> a negative binomial regression.
>>
>> First, I tried to use the function glm.nb of package MASS in R and I had a
>> problem with ensuring that the model will realize the data are for one
>> unique participant (possible correlations in a group of observations).
>>
>> Then, I realized that I can use glmmPQL of package MASS or glmer of
>> package lme4 and use the family negative binomial in it's family link.
>>
>> The question is I would like to know in which part of the model I can
>> embed the offset (logarithm of the number of days of treatment) also how
>> should I insert the time-constant observations for an id (such as gender
>> and baseline age in the df)?
>>
>> My latest attempt was:
>>
>> (glmmPQL (event ~ treatment + offset (log(person.time)) ,
>> random= list (id=~1, gender=~1, baseline.age=~1),
>> family= negative.binomial (theta=1.75), data=df ))
>>
>>
>> which faced with a memory-related error (probably because of the wrong
>> code). data example:
>>
>> 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))
>>
>>
>> Thank you for your time and considerations,
>>
>> 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