# Trying to determine which distribution to use for my percentage data for mixed effects model

I am seeing a lot of different answers to percentage data, either beta or binomial with a logit link and not to use poison distribution because it isn't count data. My response variable is retention efficiency for different food types ((Incurrent food - excurrent food)/ incurrent food) *100. There are 5 different food types. I am looking to see if the sponges from different regions and genus differ in their consumption of the five food types. I am attaching a histogram of the data which has more values closer to 1 or 100% retention (none are actually 100%). I am wondering what distribution would be best at fitting my data which would be continuous proportion I think but the data is obviously not normal. I will probably be doing some sort of generalized linear mixed-effects model

• Do you have values that are 100% and 0%? Or are all observations between those two numbers? – Mark White Apr 6 '20 at 15:53
• all are between 0 and 100, no 0% or 100% – Michael Apr 6 '20 at 16:32

From your histogram, it looks like you're using R. The {brms} package supports mixed models with beta regression, using the family = Beta() argument. The link function for the expected value is logit and for the dispersion parameter is log, by default.
The {gamlss} package also implements this, but they employ a less common reparameterization of the beta distribution.