Hi Holger/Justin, I had a question that Miya hinted on in her earlier email. So the question is whether to use the covariates or the pscores in MatchIt. The response was that we should estimate the pscores first, and then match on them using MatchIt, and not to enter the covariates in MatchIt. So I interpreted it as something like this. matches <- matchit(D~pscores, method="nearest", data=newdata...) However, it seems like MatchIt does not work that way. In the documentation for MatchIt, we are supposed to enter a formula, which MatchIt then takes to estimate distance measures and match on those distance measures. So the command should look like this. matches2 <- matchit(D~X1+X2+X3+X4+X5, method="nearest", data=data, distance="logit") With this, MatchIt will calculate pscores using the logit link, and then match on the pscores. In the first way of doing it, matchit will run a logit regression of D on our manually calculated pscores, and then match on the resulting probabilities, which are not pscores. I've done it both ways, and the matched datasets are identical. However, this could be due to the fact that there is a direct relationship between pscores and the subsequent probabilities produced by a logit of D on pscores. It seems like the first way of doing it is not actually correct, but the answers just happen to be the same. If you take the second way of doing it and then call the distance (matches2$distance), the resulting output is exactly the same as our manually calculated pscores. To sum up, it seems as if we should be inputing the actual covariates in MatchIt in order to match on pscores. Otherwise, we are matching on some other probabilities which result from a logit of D on pscores. Am I interpreting everything correctly? Thanks Patrick