Message-ID: <4E9521DF-59BB-43BA-9DBC-6097A97EB987@gmail.com>
Date: 2023-03-24T10:36:42Z
From: Mollie Brooks
Subject: Question about proportion data in binomial glmm
In-Reply-To: <CAJuCY5wBj8FZZJ+G8fw5Bbiuq=cUH7k9nUgDMPWsndN3QvMEEA@mail.gmail.com>
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 at 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
> Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
> thierry.onkelinx at inbo.be
> Havenlaan 88 bus 73, 1000 Brussel
> www.inbo.be
>
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>
> Op vr 24 mrt 2023 om 02:39 schreef rtfiner <rtfiner at 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
>>
>> [[alternative HTML version deleted]]
>>
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>>
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