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Steve Coy: What do you think of the present state of the art in high end (>99.9 percentile) IQ testing? Have you looked at them at all? Which high end tests, if any, most impress you? Least? How might the people engaged in this work improve their methodologies? (I am not myself involved in this work, but I know some who are or have been, e.g. Nikos Lygeros and Kevin Langdon.) Dr. Arthur Jensen:
I know very little about the testing of "general mental ability" at the
very high end. The only test of this type I have seen (years ago)
was by Langdon, who sent it to me. It undoubtedly shows reliable
individual differences, but I have never come across any evidence of its
statistical properties or its construct validity. I have been
under the possibly false impression that there has been little serious
or professional research effort devoted to these types of tests.
I recently read an article on some of the characteristics of youths who
are above the 99.9%ile which has some validity data, but these 320 subjects
were identified by high scores on the SAT-M when they were 13 years old.(
Lubinski, D..et al. (2001). Top 1 in 10,000: A 10-year follow-up of the
profoundly gifted. J. Applied Psychol., 86, 718-729. )
Steve Coy: Do you believe it is possible, even in principle, to properly norm a high end test in the score regime where exceedingly few people are expected to exist in the population, take the test, or participate in its norming? Dr. Arthur Jensen: I think it possible in principle, but it would be a most difficult undertaking in practice because of the problem of screening enough people to find a large enough sample. The studies of super-gifted school kids have had it relatively easy, because of the schools' identification of the gifted through their testing programs, special classes for high IQ pupils, etc. Probably the easiest way to find adults with IQs>175 would be to advertize for the cooperation of persons who had been identified as "gifted" while in school, then screen those who come forth. Steve Coy: Is it possible to quantify the self-selection effect, which has been proffered as an explanation for the observed high incidence of very high IQ scores on these tests, much higher than would be expected under the assumption that the testees were randomly selected from the general population? Dr. Arthur Jensen: This is a really tough one. The interaction of ability level with interests and lifestyle confounds selection. I daresay you will find few Mensa or Mega members with few or no intellectual interests, for example, although there may be people out there in the population who are very bright but have few such interests. There is also self-selection at the top end. How many Nobel Prize winners, or members of the National Academy of Sciences are in any of the high IQ societies? I was struck by the fact that the Berkeley chapter of Mensa, with its many members, had only one member who was on the faculty of UC Berkeley, although I'm sure some large percentage of them could qualify if they wished to join. And I know a Nobel Prize winner who was invited to join Mensa, but he had no interest in it and declined the invitation. It has been my (untested) impression that if IQ and achievement could be correlated in the whole population, members of HI-IQ societies would ne among those who tend to lower the correlation, falling below the regression line (of achievement regressed on IQ). Most conventional IQ tests have a general knowledge-achievement component which makes the test an amalgam of both ability and achievement and particularly skews the high end of the IQ distribution. Steve Coy: Supposing the self-selection effect could be quantified, so that we can estimate the prior distribution from which testees are drawn, can we then somehow obtain a reasonable estimate of the conditional distribution for a given test describing the probability that a person with a given IQ/g will obtain a given score? (From that, appliying Bayes' theorem, we could invert the conditional probability to obtain the distibution of IQ/g corresponding to a given score.) Dr. Arthur Jensen:
The problem with testing such propositions is that we don't have an absolute
or ratio scale of ability, or even an interval scale, so we can't know
if the units of measurement are equal throughout the full range of the
scale. This is partly why reaction times (to stimuli or cognitive
tasks of varying complexity) has become interesting to me - we're operating
with a true physical scale, which permits answers to questions about distribution
parameters that can't be answered with conventional psychometric tests.
Your Bayes' theorem idea is excellent, but I don't see how it would work
(i.e., be statistically tested) unless some part
of the distribution
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