Do you have any materials on epidemiological meta-analyses? [...] I still haven't found any good resources on how to handle the problems in epidemiology or population-level correlations.
Not to hand. But (as you've found) I doubt they'd tell you what you want to know, anyway. The problems aren't special epidemiological phenomena but generic problems of causal inference. They just bite harder in epidemiology because (1) background theory isn't as good at pinpointing relevant causal factors and (2) controlled experiments are harder to do in epidemiology.
If I were in your situation, I'd probably try running a sensitivity analysis. Specifically, I'd think of plausible ways confounding would've occurred, guesstimate a probability distribution for each possible form of confounding, then do Monte Carlo simulations using those probability distributions to estimate the probability distribution of the systematic error from confounding. This isn't usually that satisfactory, since it's a lot of work and the result often depends on arsepulls.
But it's hard to do better. There are philosophers of causality out there (like this guy) who work on rigorous methods for inferring causes from observational data, but as far as I know those methods require pretty strong & fiddly assumptions. (IlyaShpitser can probably go into more detail about these methods.) They also can't do things like magically turn a population-level correlation into an individual-level correlation, so I'd guess you're SOL there.
But (as you've found) I doubt they'd tell you what you want to know, anyway. The problems aren't special epidemiological phenomena but generic problems of causal inference. They just bite harder in epidemiology because (1) background theory isn't as good at pinpointing relevant causal factors
I've found that there's always a lot of field-specific tricks; it's one of those things I really was hoping to find.
This isn't usually that satisfactory, since it's a lot of work and the result often depends on arsepulls.
Yeah, that's not worth bothering with.
...(
How much confidence do you place in the scientific theory that ordinary matter is made of discrete units, or 'atoms', as opposed to being infinitely divisible?
More than 50%? 90%? 99%? 99.9%? 99.99%? 99.999%? More? If so, how much more? (If describing your answer in percentages is cumbersome, then feel free to use the logarithmic scale of decibans, where 10 decibans corresponds to 90% confidence, 20 to 99%, 30 to 99.9%, etc.)
This question freely acknowledges that there are aspects of physics which the atomic theory does not directly cover, such as conditions of extremely high energy. This question is primarily concerned with that portion of physics in which the atomic theory makes testable predictions.
This question also freely acknowledges that its current phrasing and presentation may not be the best possible to elicit answers from the LessWrong community, and will be happy to accept suggestions for improvement.
Edit: By 'atomic theory', this question refers to the century-plus-old theory. A reasonably accurate rewording is: "Do you believe 'H2O' is a meaningful description of water?".