This is probably a really basic question, but it's the first time I've created a model that defines Poisson as its error family.
In setting up my variables to make the model, should I be concerned about whether or not predictor variables are normally distributed, and if not, should I be attempting to transform them to make them normal? Or alternatively, should the residuals of simple regressions between each predictor and the response variable be normally distributed? Or is this something I look at overall, once the model is made, by looking at a histogram of the residuals of the full model? Or, does the normal distribution not even apply in this case because I have specified Poisson errors?