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

Ben Bolker bbo|ker @end|ng |rom gm@||@com
Thu Jul 8 16:38:09 CEST 2021

   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
> Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
> thierry.onkelinx using inbo.be
> Havenlaan 88 bus 73, 1000 Brussel
> www.inbo.be
> ///////////////////////////////////////////////////////////////////////////////////////////
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to say
> what the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
> ///////////////////////////////////////////////////////////////////////////////////////////
> <https://www.inbo.be>
> 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
>> De informatie in dit bericht is uitsluitend bestemd voor de geadresseerde.
>> Aan dit bericht en de bijlagen kunnen geen rechten worden ontleend. Heeft u
>> deze e-mail onbedoeld ontvangen? Dan verzoeken wij u het te vernietigen en
>> de afzender te informeren. Openbaar maken, kopiëren en verspreiden van deze
>> e-mail of informatie uit deze e-mail is alleen toegestaan met voorafgaande
>> schriftelijke toestemming van de afzender. Het Radboudumc staat
>> geregistreerd bij de Kamer van Koophandel in het handelsregister onder
>> nummer 80262783.
>> The content of this message is intended solely for the addressee. No
>> rights can be derived from this message or its attachments. If you are not
>> the intended recipient, we kindly request you to delete the message and
>> inform the sender. It is strictly prohibited to disclose, copy or
>> distribute this email or the information inside it, without a written
>> consent from the sender. Radboud university medical center is registered
>> with the Dutch Chamber of Commerce trade register with number 80262783.
>>          [[alternative HTML version deleted]]
>> _______________________________________________
>> R-sig-mixed-models using r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> 	[[alternative HTML version deleted]]
> _______________________________________________
> R-sig-mixed-models using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
Graduate chair, Mathematics & Statistics

More information about the R-sig-mixed-models mailing list