> If this is fairly standard practice, then an afternoon birthday surgery would be an emergency situation and, hence, more deadly
This is spot on. The causality can be both ways.
Note that it would be interesting to dig into what is really computed here, because the whole wording seem intentionally sensationalistic.
1) "23% more likely to die" seems _huge_, but it applies to an already very small chance. The mortality rate just goes from 5.6% to 7%. Using this logic, moving from 0.1% mortality rate to 0.3% would mean "you are 3 times more likely to die".
2) Comparing mortality rates only make sense if the distribution of operation complexity are identical for these days. As the parent post suggest, it seems very likely that low complexity operations are postponed after a surgeons birthday.
3) Where are the confidence intervals? I refuse to even consider looking at a statistics if error boundaries and significance metrics are not provided.
That may very well all be provided in the underlying paper, but the article itself does not really discuss these points.
> 1) "23% more likely to die" seems _huge_, but it applies to an already very small chance. The mortality rate just goes from 5.6% to 7%. Using this logic, moving from 0.1% mortality rate to 0.3% would mean "you are 3 times more likely to die".
But that is indeed precisely what it means. The 737 MAX might have increased the accident rate from 1 in a million to 3 in a million, and that would have been a tripling. That is not sensationalistic.
> 3) Where are the confidence intervals?
In the paper: "(7.2% v 5.6%; adjusted difference 1.6%, 95% confidence interval 0.4% to 2.8%; P=0.01)"
It's about the success of surgery on that surgeon's birthday, and calculating the implications of switching the surgery types etc etc, while in a real world situation you'd just use the other surgeon - which hopefully has another birthday. I agree there's gonna be some smaller effect even then, but less and less the more surgeons you have and the more randomly distributed their birthdays are.
This is spot on. The causality can be both ways.
Note that it would be interesting to dig into what is really computed here, because the whole wording seem intentionally sensationalistic.
1) "23% more likely to die" seems _huge_, but it applies to an already very small chance. The mortality rate just goes from 5.6% to 7%. Using this logic, moving from 0.1% mortality rate to 0.3% would mean "you are 3 times more likely to die".
2) Comparing mortality rates only make sense if the distribution of operation complexity are identical for these days. As the parent post suggest, it seems very likely that low complexity operations are postponed after a surgeons birthday.
3) Where are the confidence intervals? I refuse to even consider looking at a statistics if error boundaries and significance metrics are not provided.
That may very well all be provided in the underlying paper, but the article itself does not really discuss these points.