I also have a national sample of comparable individuals, along with the same continuous predictor and binary outcome. I will duplicate the above approach. Though all individuals in the second dataset also received an intervention after the collection of the continuous variable and before the outcome.

I am debating about whether it is feasible to also merge these two datasets together and predictor the binary outcome with the continuous variable while controlling for and testing the effect of the intervention status?

I wonder if I can do this or what I need to think about. I would assume (and also test) that the only difference between the datasets is that the national group got an intervention and background characteristics are comparable between datasets. Then examine the effect of the intervention on the outcome.

I am feeling that I may need to run a multi-level model. Then look to see if dataset of origin was a significant predictor (AKA intervention status). Though, I will only have two datasets of origin (local and national), so two groups in level two of the model.

**So taken home question, can I merge these sets together and test the predictive value of the continuous variable as well as effect for which dataset data came from using a multi-level model?**

Any thoughts?