I am performing exact matching on a set of continuous and categorical covariates. Once the matched (via MatchIt) is performed, I use logistic regression to estimate the effect of my treatment variable on a binary outcome. At this stage, I include all the covariates used in the matching procedure, as I want to isolate the underlying effect of the treatment as much as possible even when perfect balance has been achieved (please correct me if this is a wrong choice).
However, I have a doubt regarding the estimation procedure. Do I mandatorily need to include weights estimated in the matching step, as weights in the glm model? When I do so, the estimates change a bit compared to the models without weights.
Thanks in advance for your help!