I am a non-statistician PhD student working on a project that has involved some propensity score matching (PSM). I had initially assumed that propensity scores would represent the probability of each patient receiving the outcome of interest given their baseline characteristics. However, everything I read subsequently suggested that propensity scores represent the probability of each patient being allocated to a treatment group.
This was my new understanding of PSM until I completed the analysis and a senior statistician on the project commented that I have misunderstood PSM altogether as propensity scores should be calculated to represent the probability of each patient receiving the outcome of interest.
I am not sure how to square this with my reading around PSM, although I am also conscious that I cannot easily read many of the technical papers in the field. Is anyone here able to help me understand whether propensity scores should represent the probability of treatment or outcome, and how confident I should be when replying to this statistician?