Thank you for the brms package. I’ve the custom family vignette using beta-binomial as an example. I’m curious why beta-binomial never made it into BRMS as one of the distributions?
log( number of people whose browser crashed +1 ) ~ offset(log(total # of people)) + other_vars
using a gaussian. I model both the mean and sigma of the guassian( I guess i could have also used a negbinomial family too)
To get fitted values i do something like
exp( predict(model) - log(total # of people))
to get a rate.
Sometimes this ratio is greater than 1. I would imagine the beta-binomial would fix this domain issue of the predictor and the overdisperson too, but i’m unwilling (my choice!) to implement the custom family so i live with my capping fitted to 1 approach.
An alternative is to model the logit of the rate i.e.
logit( (#of people who crash+1)/(# of people)
Nevertheless, thanks much for the awesomeness that is brms.
Thanks in advance