Dear all, (Yet another question about response variables in [0, 1]). I'd like to fit models, that include random effects, to response variables in [0, 1] (i.e., they can take any value betwee 0 and 1, including 0 and 1). The response variables are averages of values that, themselves, are not proportions nor binary variables[1]. I'd like to avoid *zero-one-inflated (beta) models* (available, e.g., in brms), because I do not think that the 0s and 1s are governed by a different process than the values in (0, 1). Using a *beta model* (e.g., as available in glmmTMB) after transforming the response via the sometimes recommended (e.g., https://cran.r-project.org/web/packages/betareg/vignettes/betareg.pdf) (y * (n?1) + 0.5) / n does not seem ideal, since it is not clear what "n" should be, and I have about 5% of the values exactly 0 or 1. An alternative would be a *fractional response model*, with a binomial model and accounting for overdispersion. In https://stats.stackexchange.com/a/233664, using glmer, it is suggested that accounting for overdispersion can be done adding a random effect to each observation (or row of the data); we would also pass a weights vector to avoid the warning about non-integer values. But an update from January 2018 indicates that might not be a valid approach (and my own experiments with my data make me uneasy). Instead of glmer, I could fit a binomial model using MCMCglmm or INLA, both of which accomodate observation-level random effects (I guess I could try this with brms, too). I am not sure this is sensible, though, for this type of response variable. Any suggestions? Thanks, [1] One of the variables, for example, is the Jensen-Shannon divergence between two distributions, rescaled from [0, log(2)] to [0, 1] -- Ramon Diaz-Uriarte Department of Biochemistry, Lab B-25 Facultad de Medicina Universidad Aut?noma de Madrid Arzobispo Morcillo, 4 28029 Madrid Spain Phone: +34-91-497-2412 Email: rdiaz02 at gmail.com ramon.diaz at iib.uam.es http://ligarto.org/rdiaz
fractional response models with random effects (or another question about [0, 1] response)
1 message · Ramon Diaz-Uriarte