If your are considering a poisson distribution your response y should the "total number of claims": Model Total Number of Claims = gender age / type3 dist = poisson link = log offset =log_time ... View more

You should include the offset term in your model statement since time of insurance coverage "Insured Month" is not the same across customers.  Assume you are interested in estimating the rate of claim by month (subject-month). In a simple Poisson regression model: log(λ) = β X + log(time)  + e Using the GENMOD PROCEDURE: data mydata; set mydata; log_time = log(Insured_Month); run; proc genmod data=mydata; class gender; model y = gender age / type3 dist = poisson offset = log_time; run; If you are interested in calcluating the incidence of claim by subject-year, calculate log_time as  log(Insured_Month/12); If your data appear to be overdispersed (i.e. more variation than expected under a poisson model E(Y) = VAR(Y) =λ)  consider using a negative binomial distribution. If the data appear to be zero-inflated (more zeros than expected under a poisson model)  consider using Zero Poisson Inflated (ZIP) model. ... View more