I am interested in analyzing the effect of a specific change in traffic conditions on the amount of road accidents in a city.
I need to select a comparison group; my approach is to select from possible candidates, the city\district that was in the past most similar to the city being investigated .
Monthly data is available to me for all the cities.
However, I do not know if I should take as the comparison group the city most similar to mine comparing across the months, or rather sum the months, and use the city most similar to mine judging by the years.
I do not have access to a transportation expert whom I could ask for advice that would be relevant to the specific situation.
Are there statistical considerations to make the choice?
-----Added for clarification----
The way I judge the similarity between two cities:
For each city in the control group, there is a monthly amount of accidents, C(t). For the treatment group, I will denote the amount M(t). If the treatment is similar to the control group, then in the period before the treatment M(t+1)/M(t) = C(t+1) / C(t).
Which means that the rate of change is the same between the control and the treatment group. As far as I understand, this assumption allows me to use difference -in-differences to test for the effect of the treatment.
This is based on the procedure descirbed in the book "Observational Before-after Studies in Road Safety" \ Ezra Hauer.
However, he doesn't address there the question whether I should work with the monthly data, or sum it and select according to the yearly data.