Now that I’ve started to think about it, the estimation of the measurement error might be a problem.
First we need to keep in mind the difference between precision and accuracy. Re-tests will only help with precision, obviously.
Moreover, given that we’re trying to measure g, it happens to be unobservable. That makes estimates of accuracy somewhat iffy. Maybe it will help if you define g “originally”, as the first principal component of a variety of IQ tests...
On the other hand, I think our measurement error estimates can afford to be guesstimates and as long as they are in the ballpark we shouldn’t have too many problems.
As to the empirical datasets, I don’t have time atm to go look for them, but didn’t US Army and such ran large studies at some point? Theoretically the results should be in public domain. We can also look at proxies (of the SAT/GRE/GMAT/LSAT/etc.) kind, but, of course, these are only imperfect proxies.
Now that I’ve started to think about it, the estimation of the measurement error might be a problem.
First we need to keep in mind the difference between precision and accuracy. Re-tests will only help with precision, obviously.
Moreover, given that we’re trying to measure g, it happens to be unobservable. That makes estimates of accuracy somewhat iffy. Maybe it will help if you define g “originally”, as the first principal component of a variety of IQ tests...
On the other hand, I think our measurement error estimates can afford to be guesstimates and as long as they are in the ballpark we shouldn’t have too many problems.
As to the empirical datasets, I don’t have time atm to go look for them, but didn’t US Army and such ran large studies at some point? Theoretically the results should be in public domain. We can also look at proxies (of the SAT/GRE/GMAT/LSAT/etc.) kind, but, of course, these are only imperfect proxies.