Could you please explain or provide some reference why we need to aggregate the data when the event is not recurrent or rare? I saw papers using time varying covariates when modeling non-recurrent event incidence rate, so the data is restructured to repeated measurements, with the outcome being 0 or 1 and offset is time between two measurements. Are they doing this in a wrong way?
l am also wondering if there is a minimum number of events requirement for multiple Poisson regression, when the event is really rare? For example, only 5 incidence events out of 500 individuals? Is it possible to do any model with covariates?
