[R-sig-ME] GLMM for proportions

[Ben Bolker]

  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
>