Dysgenics for whom?
A replication of 2 prior studies using a new dataset
Some time ago, we published studies showing that the negative correlation between intelligence and fertility varies by other factors. Specifically, we found that it varies by religiousness and conservatism, in that leftists and unreligious people show stronger dysgenic effects. These results were based on reasonably large samples. The largest was the cumulative GSS dataset with decades of representative Americans, resulting in tens of thousands of subjects, and still a large number of we subset to people with completed fertility (age 50+). Second, a replication in the Vietnam Experience Study, which has 4500 American former soldiers measured at age 38. This is somewhat problematic because men aren’t done reproducing at that age, also not in 1985 which is when the data is from.
So I decided I wanted to dig into these findings and conduct a large-scale comprehensive replication. I surveyed Americans on Prolific and only targeted those with completed fertility in ages 50-69. I wanted to try out the Multifactor General Knowledge Test on another sample. It has an odd response format, where it shows you 10 options and says “Pick the 5 things that are X and don’t pick any things that aren’t X”. You get 1 point for each correct thing you picked and 1 point for each incorrect thing you didn’t pick. There are 32 questions, and thus one can get 320 points at most. We shall see that this format presents severe psychometric issues that I didn’t previously see, and Seb Jensen didn’t note them in our paper on this test. In addition, I put together a few questions to measure overall religiousness, a standard US-style left-right scale, and a checklist for mental illness diagnoses. Thus, putting all of this together, we should be in a decent position to find those pesky effects. They are hard to find because the intelligence fertility correlation is weak to begin with, about 0.10, and we are looking for relatively week interactions with that, say, that changes it to 0.00 or 0.20. This require a lot of statistical precision.
This post is basically the preview of the academic write-up of this article, since I just finished the analyses after waiting some months for the data collection to finish.