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?".
Hmm. Based on the epidemiology papers I've skimmed through over the years, there don't seem to be any killer tricks. The usual procedure for non-experimental papers seems to be to pick a few variables out of thin air that sound like they might be confounders, measure them, and then toss them into a regression alongside the variables one actually cares about. (Sometimes matching is used instead of regression but the idea is similar.)
Still, it's quite possible I'm only drawing a blank because I'm not an epidemiologist and I haven't picked up enough tacit knowledge of useful analysis tricks. Flicking through papers doesn't actually make me an expert.
True. Even though doing experiments is harder in general in epidemiology, that's a poor excuse for not doing the easy experiments.
Ah, I see. I misunderstood your earlier comment as being a complaint about population-level correlations.
I'm not sure which variables you're looking for (population-level) correlations among, but my usual procedure for finding correlations is mashing keywords into Google Scholar until I find papers with estimates of the correlations I want. (For this comment, I searched for "smoking IQ conscientiousness correlation" without the quotes, to give an example.) Then I just reuse those numbers for whatever analysis I'd like to do.
This is risky because two variables can correlate differently in different populations. To reduce that risk I try to use the estimate from the population most similar to the population I have in mind, or I try estimating the correlation myself in a public use dataset that happens to include both variables and the population I want.
You never try to meta-analyze them with perhaps a state or country moderator?