[R-sig-ME] GLMM for proportions

[poulin]

Yes I mean milliseconds instead of seconds but I made a mistake. Its not 
milliseconds but 0.01s. My bad.

But as I explained in my second mail it's more going from fames (lasting 
0.04s) to 0.01 s.

Actually the main problem was that each video was not lasting the same 
time. Hence it is not possible to analyse time without reference to the 
total lasting of the video

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 16:27, Ben Bolker a écrit :
>    Complementing Thierry Onkelinx's answer:
>
>    This is more generally a GLM (rather than GLMM) question.
>
>    Can you clarify a little bit more?  When you say "ms instead of s" do
> you mean milliseconds rather than seconds?
>
>    If you actually have durations, a Gamma(link="log") or plain
> log-Normal analysis (i.e. log-transform and then linear model) might
> work. In either case, values of exactly zero will be technically
> problematic, and will require you to think a bit more about the
> data-generating process.
>
>    If you have fractions of a time interval then Beta regression might
> work (in glmmTMB or brms or mgcv), or you can logit transform or
> (old-fashionedly) arcsin-sqrt transform ...
>
> On 2018-06-06 10:13 AM, poulin wrote:
>> 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
>>
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