R: 1:n propensity score match using MatchIt

Question

I have done a 1:5 propensity score matching in R using MatchIt package(ratio=5), but how can I know which one of the "5" matches the "1" best and which the worst? And from the exported outcome, I see a variable called "distance", what does it mean? Can I use it to mearsure the fitness of macthing?

Answer 1

distance is the propensity score (or whatever value is used to create the distance between two units). See my answer here for an explanation. It will be empty if you use Mahalanobis distance matching.

To find who is matched to whom, look in the $match.matrix component of the output object. Each row represents one treated unit, whose rowname or index is given as the rowname of this matrix. For a given row, the values in that row represent the control units that the treated unit was matched to. If one entry is NA, that means no match was given. Often you'll see something like four non-NA values and one NA value; this means that that treated unit was only matched to four control units.

If you used nearest neighbor matching, the columns will be in order of closeness to the treated unit in terms of distance. So, those indices in the first column will be closer to the treated units than the indices in the second column, and so on. If another kind of matching was used, this will not be the case.

There are two aspects to the "fitness" of the matching: covariate balance and remaining (effective) sample size. To assess both, use the cobalt package, and run bal.tab() on your output object. You want small values for the mean differences and large values for the (effective) sample size. If you are concerned with how close individuals are within matched strata, you can manually compute the distances between individuals within matched strata. Just know that being close on the propensity score doesn't mean two units are actually similar to each other.