I found some genetically informative studies on the benefits of marriage:

These studies control for genetic and shared environmental confounding in various ways and generally find some benefits of marriage on crime reduction and mental health/well-being. The benefits from non-controlled studies are found to be exagerated, of course, because they don’t control for the omnipresent genetic confounding. I posted one study on Twitter:

JayMan (J) doesn’t agree. In private, he argued that twin control studies don’t rule out all confounding. This is true, they fail to rule out a very tiny amount of genetic confounding — MZ twins are not exactly genetically identical, but they are very close. Furthermore, there is the possibility of non-shared non-genetic confounding.

I wrote:

Given that non-shared non-genetic variance is noise, one can indeed infer causation. Within MZ associations are strong evidence of causation.

(Infer here was perhaps too strong a phrasing. I meant it probabilistically.)

In J’s words:

No, because it’s not *all* noise (obviously so in the case of sexual orientation in discordant twins). Some of it is developmental variation. Some of it is the result of pathogens/other environmental insults.

However, he is incorrect:

Evidence means that the posterior probability is larger than the prior. In this case, a within MZ association rules out confounding due to A and C pathways. This is important because A confounding is probably the largest source of confounding, hence ruling it out increases the probability of all remaining options including causal connection. This being a longitudinal study (with a control too) also rules out reverse causation, further increasing the probability of forward causation.

Your argument is ignoring the probability change. To generalize and illustrate: one cannot declare something not evidence just because it does not rule out all possible alternative interpretations. If we know that x must be one of 1, 2, … 10. Ruling out that it is 1-8 is strong evidence that it is 9, even if it is still possible that it is 10. Assuming equiprobable options, the probability increases by a factor of 5 (from 10% to 50%).

To give a concrete but simplified example. Suppose that whenever we find an association between two human variables like these, 60% of the time it is due to genetic confounding, 20% of the time it is due to shared environmental confounding, 10% of the time it is due to non-shared non-genetic confounding (this includes the developmental variation that J mentions) and 10% of the time it is causal. So, the prior probability of true causality is only 10%. However, if we then find that this relationship holds when we control for genetic and shared environmental confounding, the posterior probability of causality is now 50%. This is because only non-shared non-genetic confounding and true causality remains as possible options, both with 10% prior probability, and thus with 50% of the posterior. Thus, this represents a 5x increase in the probability. By one common Bayesian standard, this represents strong evidence.

Back in reality, a given link between two variables will be some mix of variance pathways (e.g. 50% genetic, 30% shared environmental confounding, 20% causal), not only a single. This does not change anything substantial about the results, only makes it more complicated. (Proof of this is left to the reader!)

5 Responses

  • To state clearly for readers, no, twin controls aren’t evidence of causation between one environmental factor to another.

    Of the four studies you cite, three are from the same dataset (the Add Health). All the variables there were self-reported, by the way.

    To give a concrete but simplified example. Suppose that whenever we find an association between two human variables like these, 60% of the time it is due to genetic confounding….Thus, this represents a 5x increase in the probability. By one common Bayesian standard, this represents strong evidence.

    The problem here is that all your probabilities are completely made up. Strictly speaking, yes, a positive twin control does make it more likely that the observed relationship is causal. But how likely was this to start with? Are we going from one small number to another somewhat less small number? A priori, given other evidence, the odds of that this is causal is low. But this isn’t really good science. We need a way to definitely answer the question. And as I said elsewhere, how do you rule out pre-existing non-genetic twin differences as a causal factor? No one seems to address this. This is hardly a trivial matter (particularly considering non-genetic developmental twin differences are known to exist, exemplified by fingerprints, handedness, etc.). This is not even to mention that these associations in positive twin controls could just be false positives (especially in this case given small samples and fully self-reported data).

  • Emil Kirkegaard

    The numbers doesn’t matter much. They only illustrate the point. But we do know that most confounding is A+C, which means that MZ controls provide relatively strong evidence of causation. It is really not a complicated issue. (No one seems to address this. <— It was addressed).

  • Aldo

    What do you make of this post by RaceRealist88/NotPoliticallyCorrect :

    notpoliticallycorrect.me/2017/11/23/iq-test-construction-iq-test-validity-and-ravens-progressive-matrices-biases/

    It looks like the site’s primary writer is now denying IQ’s use for determining intelligence. He’s also posted these articles:

    notpoliticallycorrect.me/2017/10/29/most-human-performance-traits-do-not-lie-on-a-bell-curve/

    notpoliticallycorrect.me/2017/07/06/do-physiologists-study-general-intelligence/

  • Emil Kirkegaard

    I think it is very suspicious of self-promoting sockpuppetry that I get a lot of random people with new users, emails without any history etc. always asking me to comment on that one blog.

  • waffleironmarch

    I ended up here after some googling inspired by reading the comments section of one of Jayman’s older blog posts wherein Emil was saying that hereditary contribution to within-group differences didn’t necessarily imply that the same held true to between-group differences.

    After following these links to RR’s blog where s/he’s trying to argue against the validity and significance of IQ tests, I really would like to see both Emil and Jayman tackle the claims made therein. So. I don’t think there’s any sock puppetry going on here. It’s a genuine theoretical concern that a lot of other HBDers should engage with.

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