"Unmarried twenty-somethings are more likely to be depressed, drink excessively, and report lower levels of satisfaction than their married counterparts"
Let's all say it together: Correlation is not causation.
I've seen elsewhere that financial troubles often herald divorce. If the only marriages that can last are ones where someone's making a premium, then of course you'll see one.
I'm sorry, but that seems to be about earnings, not about happiness or drinking habits. Am I missing something? (It also says that women experience a penalty, whereas the original article asserts positive correlations for both men and women.)
The alternative theory being (1) that marriage causes men to invest more in their jobs and women to invest more in children, but (2) that the correlation between women's marriage with happiness, and between the historical decline of marriage and raising of children with increasing female unhappiness, is acausal?
Unfortunately, making understanding the real world is not easily reducible to propositional logic. Since you seem interested in pedantry, the technical thing to say is that you must use Bayesian inference and reasonable priors.
In this case, explanations for A and C being correlated without A causing C are strongly related to explanations for why A and B might be correlated without A causing B. (E.g., people who get married are predisposed to be successful.) Evidence, which necessarily can't be in the form of a randomized controlled experiment and yet can still be very strong, that A in fact causes B greatly reduces ones belief that A might not be causing C. My previous comment was asking whether you would defend alternatives that I find to be very unlikely, like a hypothetical predisposition for people to both get married and be happy but which is completely independent from the increase in earnings.
Since we're talking about belief rather than what we can prove, I think it's extremely plausible for the causation in question to go the other way. Given the choice, would you rather date / marry someone who was happy and healthy or someone who was depressed and drinks too much?
All science is about belief. Randomized controlled trials are useful not because they convey mathematical proof, but because they give strong evidence for beliefs.
Your question doesn't help. For the sake of argument we have granted that marriage causes men to earn more money. And yet, I would still prefer to marry someone who was earning more money (or who had the potential to earn more in the future), all else being equal. This preference doesn't dispute the causation.
The causation could easily be backwards. Who wants to marry a depressed, unsatisfied drinker?
> Isn't it generally sound to assume causation until the position can be falsified?
Not really, no. Would you assume causation in the case of cereal consumption typically increasing 30% on the first Tuesday after a heavy rainfall? There are many similarly insane correlations that you wouldn't be so quick to assume causation about. It's biased to assume causation (based solely on statistics) when you want it to make intuitive sense.
>Would you assume causation in the case of cereal consumption typically increasing 30% on the first Tuesday after a heavy rainfall? //
I can't really conjure an imaginary causation because for your imagined one [?] I'm not sure what your claim is - do you mean 30% more breakfast cereal is eaten (as opposed to purchased) on the Tuesday following heavy rain, in all areas (globally??). If it were a local statistic to the USA then one could argue that when the weather is bad people stay in at the weekends and drink more, then they miss breakfast on a Monday because they're hungover, then on Tuesday they resolve to better health and so eat breakfast cereals, they of course give up on Wednesday on the whole and the cycle repeats.
There are no real causes for imagined realities so there is no gain in asking - or answering - the question if it is indeed made up.
It's entirely plausible that there is an explanation for a similarly absurd sounding but real statistic that relies on causation.
>you wouldn't be so quick to assume //
You're right, I try not assume much but FWIW I only asked if it were sound or not, not if one were likely to do it.
You say it's "biased", I don't understand what you mean. If you always assumed a causative chain when first encountering [direct, gross, longitudinal] correlation where would the bias lie?
Because unhappy people aren't fun to be around, so people don't choose to marry them? Or because depressed people are negative about their relationships, just like anything else, so don't see them as worth pursuing? It's really not hard to conjecture mechanisms for a correlation.
Absolutely not as assuming causation implies you know the directionality of the relationship. Cancer correlates pretty well with old age but you'd be pretty silly to assume that it causes old age.
By "assume causation" I meant "assume there is a causative link", which for cancer appears to be true to a degree. So if I specify and say "is it sound to assume a causative link [without specifying the cause and effect direction or that link] where a strong direct correlation is observed" (or similar wording) would you go for that?
There are many examples of course to prompt this clarification - fatness causes over-eating, bruises cause people to get hit, et cetera. There are also likely many examples where the direction of the causation is not clear - poverty and [minor] theft say.
Can you [or anyone] give an example where a causative relationship as a first hypothesis is ludicrous without questioning direction of the relationship?
I agree. Someone already in that situation will not be less depressed or more satisfied just by getting married. If anything, that's likely to make it worse in most cases.
Let's all say it together: Correlation is not causation.