[R-sig-ME] Question about proportion data in binomial glmm

[Mollie Brooks]

They have zero contribution to the log-likelihood, so they shouldn’t affect the model.

> dbinom(0, 0, 0.1, log=TRUE)
[1] 0

I can’t say if they would affect any model evaluation functionality, but they shouldn't.

Best,
Mollie

> On 24 Mar 2023, at 09.12, Thierry Onkelinx via R-sig-mixed-models <r-sig-mixed-models using r-project.org> wrote:
> 
> Dear Robert,
> 
> IMHO you should remove the cbind(0, 0) before fitting the model. There is
> no reason to keep them in the dataset.
> 
> 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 vr 24 mrt 2023 om 02:39 schreef rtfiner <rtfiner using gmail.com>:
> 
>> I have a question about how glmmtmb handles proportion data for the
>> purposes of a binomial glmm.
>> 
>> I combined my success and failure count data into a matrix using cbind(),
>> and used that as my response in my binomial glmm using glmmtmb.
>> 
>> However, despite there being a few instances of zero counts in both columns
>> and therefore an undefined proportion, the model doesn't seem to drop these
>> rows from my data set.
>> 
>> I don't get any errors or warnings when running the model, but I worry my
>> results might be biased because of this.
>> 
>> My question is: Is glmmtmb doing something like adding a tiny amount to
>> each value of my response in order to avoid dealing with undefined
>> proportion data?
>> 
>> Thank you for your help,
>> 
>> Robert
>> 
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>> 
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