[R-sig-ME] GLMM for proportions

[poulin]

Thanks Thierry for this advice. Yes I was aware of this. Actually, the 
data were obtained by analysing videos frame by frame. The video's 
resolution was such that each frame "duration" is considered to be 
0.04s. My first advice to the biologists was to use the numbers of 
frames for both number of success and failure. They did not want this 
because they want to speak (and analyse) in term of real duration. 
Hence, using ms instead of frames is multiplying the number of attemps 
by 4.

They have publish the results last year 
(https://peerj.com/articles/3227/) but someone wrote to the editor to 
tell the statistical approach was wrong and to use directly the 
proportions in the GLMM. This person did not mention that, doing this, a 
warning message was displayed.

Best regards

Nicolas Poulin
Ingénieur de Recherche
Centre de Statistique de Strasbourg (CeStatS)
http://www.math.unistra.fr/CeStatS/

Tél : 03 68 85 0189

IRMA, UMR 7501
Université de Strasbourg et CNRS
7 rue René-Descartes
67084 Strasbourg Cedex
Le 06/06/2018 à 16:24, Thierry Onkelinx a écrit :
> Dear Nicolas,
>
> The cbind(success, failure) notation is used when we aggregate (sum)
> the number of successes and failures. The data generating process
> behind it, are a series of trials which result in either success or
> failure. Hence their sum will be integer.
>
> We need to know more about your data generating process in order to
> give you sensible advice. Scaling the data by using different units is
> wrong. Compare binom.test(c(1, 9)) and binom.test(c(1000, 9000)). Both
> yield exactly the same proportion, but their confidence interval are
> very different. Why? c(1000, 9000) is much more informative than c(1,
> 9).
>
> 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 using inbo.be
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>
> ///////////////////////////////////////////////////////////////////////////////////////////
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> 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
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>
>
>
> 2018-06-06 16:13 GMT+02:00 poulin <poulin using math.unistra.fr>:
>> Dear list,
>>
>> I have a question regarding GLMM's for proportion fitted with lme4.
>>
>> Such models are fitted using the binomial family. When I fit such models, I
>> use, on the left side of the formula : cbind(success,failure).
>>
>> Problem is when, for example, data are durations (duration of success and
>> duration of failure) that are not integer numbers if speaking in seconds.
>> When fitting a GLM, one can use directly in the left part of the formula a
>> variable that is the proportion of success. When trying to do this for a
>> GLMM one will have the warning message : « In eval (family$initalize, rho):
>> non-integer # successes in a binomial glm! »
>> To avoid this, biologists I work sometimes with, used ms instead of s for
>> their duration times of success and failure but then the associated tests
>> are too powerfull...
>> I am not able to tell if the displayed warning message is of concern or not.
>> So my question is : do you think it is better to use ms instead of s or
>> directly the proportion?
>> Thanks in advance for any help that can be provided
>> Best regards
>>
>> --
>> Nicolas Poulin
>> Ingénieur de Recherche
>> Centre de Statistique de Strasbourg (CeStatS)
>> http://www.math.unistra.fr/CeStatS/
>>
>> Tél : 03 68 85 0189
>>
>> IRMA, UMR 7501
>> Université de Strasbourg et CNRS
>> 7 rue René-Descartes
>> 67084 Strasbourg Cedex
>>
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