I am using the package MatchIt in R to perform propensity score matching. I have chosen to use nearest neighbor matching with a caliper of 0.2 and since in my case i have more cases than controls i have to use the replacement=TRUE option, so that a control can be used more than once.
The graphical histogram check is satisfying and the stand.mean differences are all small with a max of 0.03 (btw any other suggestions for testing the matching?) I want to use the matched dataset to check the treatment effect after all the matching(perform logistic regression with mortality as outcome and treatment as explanatory variable now) and i am wondering if i should take into consideration the weights that were resulted from the matching. Since i used the replacement option not all observations have a weight of 1 anymore. Shall i use this somehow or can i just perform an unweighted final logistic regression on the matched data to estimate the effect of treatment.