For right comparison of two groups (cases and control), I underwent propensity score matching (PSM) accounting 8 variables which showed significant difference between the two groups: one of them is sex.
After PSM, cox proportional hazard model was also performed to evaluate association with survival.
In order to maximize the number available for analysis, PSM was done with control to case ratio=4 (K=4). However, in comparison of baseline characteristics, two groups showed significant difference in sex even after the matching (P=0.015).
I assume that this is due to high control to case ratio, and the two groups had shown dramatic difference in male proportion (45% vs 80%) before PSM.
Would this significant difference after matching be a potential point for major criticism?
I am planning to include sex for multivariate cox proportional hazard model, considering this significant difference.
Usually when comparing baseline characteristics, you would present the unmatched data. Using a propensity score does not guarantee that both groups will be balanced on any individual component of the score. It just mean that over all of the components combined, there will be an even balance. So nothing to worry about.
@Adrian Esterman
Thank you very much for your answer! It was reassuring and helpful :)
The matching is inadequatefor purpose of propensity scores.
Hope this helps,
Matt
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