I'm trying to use propensity score matching (PSM) to find matched controls. The data is not cross-sectional and it has time dependent information (monthly, quarterly, etc.). Let us say I have information from t_0 to t_N for both control units and treated units, and the event (treatment) for the treated units can happen at any time between t_0 and t_N. Is there an easy way to use propensity score matching using R or SAS to find the matched controls for each of the treated units?
Not matching, but you might want to look up marginal structural models, which essentially use propensity score based weights to balance treated/untreated cases on time invariant and time varying confounders.
For reference you can see:
Robins, Hernan, Brumback (2000) Marginal structural models and causal inference in epidemiology, Epidemiology, 11 (5): 550-560