I have monthly data on the number of people who have a disease, say, cold, within the study population, and I have the number of people that took certain medication when they had the cold. And I have an intervention time point to estimate the intervention effect.
To me it looks like I have a binomial distributed series. If I remember correctly a stationary series doesn't need to be normal, but I am not sure if I should fit a ARMA model on a series of proportions - the first problem I can think of is, the forecast might not be bounded between 0 and 1.
Please let me know if Box-Jenkins models are the right way to go here or should I use a glm type of thing allowing high order of correlations?