A comparison of methods for the analysis of binomial proportion data in behavioral research

Here we studied the performances of some of the available analytic methods applicable to the analysis of proportion data; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report the conclusions from a simulation study evaluating power and Type I error rates of these models in scenarios akin to those met by behavioral researchers and differing in sample size, cluster size and fixed effects parameters; plus, we describe results from the application of these methods on data from two real behavioral experiments.