I am using Genetic Matching to infer causality from observational data. Because I am matching with replacement, the matched Control group has multiple instances of some of the same subjects. In this case, when I am performing t-tests/non-parametric tests after matching to determine if the groups are significantly different, should I use the matched Control group with multiple instances of the same subjects? Or should I take out any repeated measures before performing these tests? Leaving them in would ensure that both the treated and control groups have the same number of subjects. Removing repeated subjects, would mean that my control group is around 60-70% of the size of my treated group.
To clarify further, these tests I am referring to are not for evaluating post-matching balance. I am matching between 2 groups where the main difference is hours of therapy (Low Dose vs High dose) and I am using matching to ensure that these groups are similar in all demographic covariates (age, gender, etc)
Then after matching, I am performing t-tests/ non-parametric tests to see if the Low Dose and High Dose group-subjects are different in terms of their recovery (functional test scores. etc). But these post-matching tests are not being performed on the covariates that were used for matching