Here's another installment of rationality quotes. The usual rules apply:
- Please post all quotes separately, so that they can be upvoted or downvoted separately. (If they are strongly related, reply to your own comments. If strongly ordered, then go ahead and post them together.)
- Do not quote yourself.
- Do not quote from Less Wrong itself, Overcoming Bias, or HPMoR.
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Health is extremely important - the statistical value of a human life is something like $8 million - so smallish looking effects can be practically relevant. An intervention that saves 1 life out of every 10,000 people treated has an average benefit of $800 per person. In this Oregon study, people who received Medicaid cost an extra $1,172 per year in total health spending, so the intervention would need to save 1.5 lives per 10,000 person-years (or provide an equivalent benefit in other health improvements) for the health benefits to balance out the health costs. The study looked at fewer than 10,000 people over 2 years, so the cost-benefit cutoff for whether it's worth it is less than 3 lives saved (or equivalent).
So "not statistically significant" does not imply unimportant, even with a sample size of several thousand. An effect at the cost-benefit threshold is unlikely to show up in significant changes to mortality rates. The intermediate health measures in this study are more sensitive to changes than mortality rate, but were they sensitive enough? Has anyone run the numbers on how sensitive they'd need to be in order to find an effect of this size? The point estimates that they did report are (relative to control group) an 8% reduction in number of people with elevated blood pressure, 17% reduction in number of people with high cholesterol, and 18% reduction in number of people with high glycated hemoglobin levels (a marker of diabetes), which intuitively seem big enough to be part of an across-the-board health improvement that passes cost-benefit muster.
This would be much more convincing if you reported the costs along with the benefits, so that one could form some kind of estimate of what you're willing to pay for this. But, again, I think your argument is motivated. "Consistent with zero" means just that; it means that the study cannot exclude the possibility that the intervention was actively harmful, but they had a random fluctuation in the data.
I get the impression that... (read more)