This seems so elementary, but I always get stuck at this point…
Most of the data I deal with are non-normal, and most of the analyses based on a GLM structure. For my current analysis, I have a response variable that is "walking speed" (meters/minute). It's easy for me to identify that I cannot use OLS, but then, I have great uncertainty in deciding what family (Gamma, Weibull, etc.) is appropriate!
I use Stata and look at diagnostics like residuals and heteroscedasticity, residuals vs. fitted values, etc.
I am aware that count data can take the form of a rate (e.g. incidence rates) and have used gamma (the analog to overdispersed discrete negative binomial models), but just would like a "smoking gun" to say YES, YOU HAVE THE RIGHT FAMILY. Is looking at the standardized residuals versus the fitted values the only, and best way, to do this? I would like to use a mixed model to account for some hierarchy in the data as well, but first need to sort out what family best describes my response variable.
Any help appreciated. Stata language especially appreciated!