As Bayesians, shouldn't this effect size cause us to update in the direction that coffee is good for health, even if we think confounding contributed to the large effect size?
Seems to me that a likely reason for a large effect size is both a causal effect of drinking coffee and confounding, added together.
As an analogy, suppose you and I are talking about a Hollywood star who has made a lot of money. I say: "The star is probably a good actor." You say: "I would just encourage people to think about this wealth level and ask whether it's plausible. The star is probably just physically attractive." Of course, the wealthiest Hollywood stars tend to be both good actors and physically attractive.
Why is a large effect size more plausible for some unspecified confounder than it is for coffee? I think some research suggests coffee induces benefits akin to caloric restriction (autophagy) among other good things: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4111762/ Should we really have a prior that an unspecified confounder can have such a large effect size? How common is that?
>Compared with nonconsumers, consumers of various amounts of unsweetened coffee (>0 to 1.5, >1.5 to 2.5, >2.5 to 3.5, >3.5 to 4.5, and >4.5 drinks/d) had lower risks for all-cause mortality after adjustment for lifestyle, sociodemographic, and clinical factors, with respective hazard ratios of 0.79 (95% CI, 0.70 to 0.90), 0.84 (CI, 0.74 to 0.95), 0.71 (CI, 0.62 to 0.82), 0.71 (CI, 0.60 to 0.84), and 0.77 (CI, 0.65 to 0.91); the respective estimates for consumption of sugar-sweetened coffee were 0.91 (CI, 0.78 to 1.07), 0.69 (CI, 0.57 to 0.84), 0.72 (CI, 0.57 to 0.91), 0.79 (CI, 0.60 to 1.06), and 1.05 (CI, 0.82 to 1.36). The association between artificially sweetened coffee and mortality was less consistent. The association of coffee drinking with mortality from cancer and CVD was largely consistent with that with all-cause mortality. U-shaped associations were also observed for instant, ground, and decaffeinated coffee.
Positive health effects from drinking sugar-sweetened coffee make me think it's not just confounding, since I wouldn't expect health-conscious people to drink sugar-sweetened coffee. But I'm suspicious regarding the "less consistent" association for artificially sweetened coffee. That makes me think that there is just too much noise in the data to know for sure, or perhaps artificial sweeteners are actually bad for you?
> As Bayesians, shouldn't this effect size cause us to update in the direction that coffee is good for health, even if we think confounding contributed to the large effect size?
If you apply this thought process to alcohol (given what we know now), what would you conclude about this approach to updating your priors based on implausible observational data?
As Bayesians, shouldn't this effect size cause us to update in the direction that coffee is good for health, even if we think confounding contributed to the large effect size?
Seems to me that a likely reason for a large effect size is both a causal effect of drinking coffee and confounding, added together.
As an analogy, suppose you and I are talking about a Hollywood star who has made a lot of money. I say: "The star is probably a good actor." You say: "I would just encourage people to think about this wealth level and ask whether it's plausible. The star is probably just physically attractive." Of course, the wealthiest Hollywood stars tend to be both good actors and physically attractive.
Why is a large effect size more plausible for some unspecified confounder than it is for coffee? I think some research suggests coffee induces benefits akin to caloric restriction (autophagy) among other good things: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4111762/ Should we really have a prior that an unspecified confounder can have such a large effect size? How common is that?
BTW, this appears to be the money quote from the paper https://www.acpjournals.org/doi/epdf/10.7326/M21-2977
>Compared with nonconsumers, consumers of various amounts of unsweetened coffee (>0 to 1.5, >1.5 to 2.5, >2.5 to 3.5, >3.5 to 4.5, and >4.5 drinks/d) had lower risks for all-cause mortality after adjustment for lifestyle, sociodemographic, and clinical factors, with respective hazard ratios of 0.79 (95% CI, 0.70 to 0.90), 0.84 (CI, 0.74 to 0.95), 0.71 (CI, 0.62 to 0.82), 0.71 (CI, 0.60 to 0.84), and 0.77 (CI, 0.65 to 0.91); the respective estimates for consumption of sugar-sweetened coffee were 0.91 (CI, 0.78 to 1.07), 0.69 (CI, 0.57 to 0.84), 0.72 (CI, 0.57 to 0.91), 0.79 (CI, 0.60 to 1.06), and 1.05 (CI, 0.82 to 1.36). The association between artificially sweetened coffee and mortality was less consistent. The association of coffee drinking with mortality from cancer and CVD was largely consistent with that with all-cause mortality. U-shaped associations were also observed for instant, ground, and decaffeinated coffee.
Positive health effects from drinking sugar-sweetened coffee make me think it's not just confounding, since I wouldn't expect health-conscious people to drink sugar-sweetened coffee. But I'm suspicious regarding the "less consistent" association for artificially sweetened coffee. That makes me think that there is just too much noise in the data to know for sure, or perhaps artificial sweeteners are actually bad for you?
Edit: I wrote some more skeptical thoughts here https://news.ycombinator.com/item?id=31602472