I'm working on propensity score matching, but I'm experiencing some problems. I am using the "propensity score matching" tool in SPSS v. 24 (but we've tried the same in R and "manual" by logistic regression). After PSM, surprisingly, my two treatment groups are even more different in terms of baseline covariates (age, % male, etc.) then they were before matching. Furthermore, the mean propensity score is also different between the treatment groups. So I suppose something is not going right here...?
I am matching on about 20 covariates. All of them, except age and eGFR at baseline, are coded as 0 and 1. I have experimented with this, leaving out some of the covariates, adding some more, but nothing really seem to work.
I have about 10.000 people in treatment group A and 90.000 people in treatment group B, so I think the amount of patients should not be the problem...
Did anyone else experience these problems and may have a suggestion where this goes wrong? Do I have to use a different method?
Thank you for your help!