What I really wanted to understand about this study: (1) whether they accounted for the number of years out of residency the physician was, and (2) whether they

What I really wanted to understand about this study: (1) whether they accounted for the number of years out of residency the physician was, and (2) whether they accounted for cumulative physician experience in some more rigorous way. I skimmed and searched with keywords rather than reading exhaustively, but I don't see a good description of these features. Re: (1), if the guidelines are correct and effective, I would expect women to score better because of the probability density of older men. That is, the average woman is younger and "closer to the data". Re: (2), if experience is helpful, I would expect those with more experience to do better. A priori, the person least likely to do well is a person who is far out from residency but who hasn't practiced a bunch. That person is more likely to be male than female (based on the above, basically, the historical consequence of systematic discrimination against women in medicine), and is less likely to have been trained to recognize symptoms uncommon in men. In their tables, they describe "Physician experience control." I don't see a rigorous definition of this. They have a section in the supplement on variable definitions where they do not describe this. What does this mean? From Table S2, you can see that the men have accrued a mean of ~14 physician experience points, while women have accrued a ~mean of 10, a tremendous difference at this sample size. Does this score refer to (1) or does it refer to (2)? If it refers to (1), then I'm not surprised that men do worse. If it refers to (2), then this is all the more surprising. Supplementary Table S2 also has incorrect labels (they seem to have duplicated female-physician / female-patient and left out the female-physician / male-patient). More confusingly, in the male-physician / male-patient section, the label appears to say that 10% of the male physicians are female. That can't be what they mean - but can anyone else interpret this? Edit -- I think this is referring to the average physician at that hospital. Not well named in the supplement, but that's OK. Finally, 25% of their data is with physicians with names that preclude gender assignment by their algorithm. If we assume that to be a mix of men and women, that group should perform somewhere between the male and female physicians. Why exclude this data from the analysis, rather than analyze it to confirm the trend? Study is here: http://www.pnas.org/content/pnas/early/2018/07/31/1800097115.full.pdf http://www.pnas.org/content/pnas/early/2018/07/31/1800097115... Supplement is here: http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115.DCSupplemental/pnas.1800097115.sapp.pdf http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...