In a factor analysis, one takes a large high-dimensional dataset and finds a low dimensional set of variables that can explain as much as possible of the total variation in that dataset. A big advantage of factor analysis is that it doesn’t require much theoretical knowledge about the nature of the variables in the data or their relations – factors are mostly determined directly by the data.
Hmm. I think I did see a mysterious note from Stockholm asking whether the above list is complete (it may have included a followup, will let you know if I can unearth it ...:-)
In Western Europe social scientists and statistical agencies have increasingly noticed "highest level of completed education" as a super factor. They basically paint a picture of two separate worlds (vastly different rates of health levels, life expectancy, media preferences, dating preferences, etc...) within society: everyone who at least got a bachelor's degree at a college/university (note that college tends to be demarcated a bit differently from the US though) and everyone who didn't, a roughly 50/50 divide in the near future. Of course this isn't the whole story: separating people for 4 or more of their formative years will inevitably create two separate worlds, no matter what you base the separation on, but I think it qualifies as a super factor that would turn up through unsupervised learning on a super dataset. It is indeed intriguing to think what other super factors might turn up. Although I really hope the people who would interpret these super factors would realize that there are a lot of self-fulfilling prophecies among them.
Surely the general factor of intelligence was worthy of a Nobel.
Then, perhaps, Democritus should receive the Nobel for atomic theory.
Spearman's g was an interesting idea, and I'm personally inclined to think it is true (for the record), but Spearman didn't prove it, even if he thought he did. As late as the 1970s, Horn -- as had his mentor R.B. Cattell, arguably the greatest IQ researcher of recent times -- denied the theory of g, maintaining that there were two g-like factors, which although correlated were not explainable by a higher-order factor.
The reigning Cattell-Horn-Carroll IQ model accepts g, but de-emphasizes it relative to group factors at the second stratum. (I'm inclined to think it emphasizes g too little.) Carroll hesitated before accepting g, being unsure about whether the massive amount of evidence he reviewed justified it.
My impression is that factor analysis has ben used less in the economics literature. For example, I haven't seen factor deco positions in the trade literature to analyze sources of comparative advantage, and not much in the institutions literature to find a few dimensions among the large number of institutional measure,
Is this your impression as well, and if not, what are your favorite references?
I just know that the fact that factors are orthogonal implies that if category factors are correlated, overall factors will include contributions from multiple categories.
It sounds like you might have a prior about how an as-yet-unrecognized super-factor might covary with intelligence, ideology, and personality type. If so, what is that prior?
That's taboo.
Hmm. I think I did see a mysterious note from Stockholm asking whether the above list is complete (it may have included a followup, will let you know if I can unearth it ...:-)
A deeper data analysis might support this guess, but I want to see that analysis.
In Western Europe social scientists and statistical agencies have increasingly noticed "highest level of completed education" as a super factor. They basically paint a picture of two separate worlds (vastly different rates of health levels, life expectancy, media preferences, dating preferences, etc...) within society: everyone who at least got a bachelor's degree at a college/university (note that college tends to be demarcated a bit differently from the US though) and everyone who didn't, a roughly 50/50 divide in the near future. Of course this isn't the whole story: separating people for 4 or more of their formative years will inevitably create two separate worlds, no matter what you base the separation on, but I think it qualifies as a super factor that would turn up through unsupervised learning on a super dataset. It is indeed intriguing to think what other super factors might turn up. Although I really hope the people who would interpret these super factors would realize that there are a lot of self-fulfilling prophecies among them.
Surely the general factor of intelligence was worthy of a Nobel.
Then, perhaps, Democritus should receive the Nobel for atomic theory.
Spearman's g was an interesting idea, and I'm personally inclined to think it is true (for the record), but Spearman didn't prove it, even if he thought he did. As late as the 1970s, Horn -- as had his mentor R.B. Cattell, arguably the greatest IQ researcher of recent times -- denied the theory of g, maintaining that there were two g-like factors, which although correlated were not explainable by a higher-order factor.
The reigning Cattell-Horn-Carroll IQ model accepts g, but de-emphasizes it relative to group factors at the second stratum. (I'm inclined to think it emphasizes g too little.) Carroll hesitated before accepting g, being unsure about whether the massive amount of evidence he reviewed justified it.
So what happens when you do this analysis and realize you've rediscovered race?
My impression is that factor analysis has ben used less in the economics literature. For example, I haven't seen factor deco positions in the trade literature to analyze sources of comparative advantage, and not much in the institutions literature to find a few dimensions among the large number of institutional measure,
Is this your impression as well, and if not, what are your favorite references?
The general factor of ideology explains why the Nobel prize hasn't been awarded to the discoverer of the general factor of intelligence.
Surely the general factor of intelligence was worthy of a Nobel.
I just know that the fact that factors are orthogonal implies that if category factors are correlated, overall factors will include contributions from multiple categories.
"A Nobel prize worthy level of seminality, or more."
I mean, just think of all the Nobels that have been given out to researchers on the general factor of intelligence.
It sounds like you might have a prior about how an as-yet-unrecognized super-factor might covary with intelligence, ideology, and personality type. If so, what is that prior?