For years it was taken for granted that the correlation between IQ and brain size is 0.4. This was the correlation cited by authoritative IQ expert Arthur Jensen in his book The g Factor and this was the figure cited in a review by leading experts in the brain-size IQ correlation: J. Philippe Rushton and C. Davison Ankney.
A correlation between 0.33 and 0.5
A 2005 meta-analysis by Michael A. McDaniel found a correlation in the mid 0.30s. Close enough to Jensen and Rushton’s 0.4, I thought.
However in the year 2000, a paper by scholars John C Wickett, Philip A Vernon, and Donald H Lee found that correcting for range restriction (when correlations are too low because the study sample is too homogeneous) and attenuation, raised such correlations from 0.35 to a potent 0.5! Corrections for attenuation was irrelevant to me because I am interested in the correlation between brain size and IQ as it is actually measured, not the correlation between brain size and some theoretically perfectly reliable IQ test that doesn’t exist. So ignoring the latter correction, it seemed that correcting for range restriction alone raised the correlation from 0.35 to at least 0.45 (an increase of 0.1!). It seemed like if anything, Jensen and Rushton erred on the low side.
A correlation of only 0.24???
However in 2015, a new meta-analysis by scholars Jakob Pietschnig, Lars Penke, Jelte M. Wicherts, Michael Zeiler, and Martin Voracek surfaced claiming the brain size-IQ correlation was only 0.24! The paper argued that the 0.4ish figure that was typically cited was inflated by publication bias and these authors went out of their way to counter this. They started by creating a list of criteria studies needed to meet for inclusion in their meta-analysis and then began recording the brain-size IQ correlation in each study. The authors write:
In cases where these criteria were met, but correlation coefficients were not reported, corresponding authors were personally contacted by email and asked to provide the relevant results.
Asking scientists to report unpublished correlations is a good way to counter publication bias, and I applaud the authors for doing so, but then they wrote something that troubled me:
In a number of studies, correlation coefficients of non-significant associations of IQ and brain volume were not reported. Whenever this was the case, corresponding authors of the respective articles were contacted and correlation coefficients were obtained through personal communications. Otherwise, following a conservative approach as described by Pigott (2009, pp. 408-409), non-significant effect sizes were set to zero.
So it sounds like, if a study says “we found an insignificant correlation between IQ and brain size” but the correlation is unreported, they contact the author to find what that correlation was. But what if the study says “we found a significant correlation between IQ and brain size” and the correlation is not reported. Did they still contact the scientist? Actively seeking out unpublished correlations that are likely to be low (insignificant correlations) while not doing the same for unpublished correlations that are likely high (significant correlations) could bias the meta-analysis downward, however elsewhere in the paper they imply that all unreported correlations were solicited, so perhaps there was no such bias. However, their practice of assigning all unknowable insignificant correlations a value of zero seems like it would indeed bias the meta-analysis downward.
The other problem with this meta-analysis is that it included many studies that suffered from range restriction. As the above cited 2000 paper of scholars John C Wickett, Philip A Vernon, and Donald H Lee found, correcting brain-size IQ studies for range restriction increases the correlation by about 0.1. So it’s likely that if all the studies in this 2015 meta-analysis were corrected for range restriction, the correlation would rise from 0.24 to 0.34.
Conclusion: The true correlation is about 0.35
I have become suspicious of meta-analyses because they seem to consistently undermine established correlations between IQ and a wide range of variables, in favor of smaller more politically correct correlations. For example, Jensen claimed the correlation between IQ and income was 0.4, but a meta-analysis claims it is only 0.25. Scholar Richard Lynn claimed that black Africans score 33 IQ points lower than British whites, but a meta-analysis claimed they only score 20 points lower. Considering that meta-analyses have tried to undermine IQ’s correlation with such Darwinian variables as income and race, it’s not surprising that they would also undermine its correlation with brain size (the most Darwinian correlate of them all).
On the other hand, it could be that the meta-analyses are accurate and that HBDers have inflated these correlation by selective reporting. However a problem with meta-analyses is that crappy studies get lumped in with good ones, and the more error that gets included, the less likely you are to find a strong correlation between any two variables.
And so it is my opinion that the best way to get the truth is to look at the very best single studies ever done. Ironically, because IQ and especially brain size are hard to measure, the single best studies do not measure both variables directly.
For example, scholars Jensen and Sinha (1993) reanalyzed autopsy data reported by Passingham (1979) on 734 men and 305 women and found, independent of body size, an overall correlation between brain mass and achieved occupational level of roughly 0.25. The typical study correlating brain-size with IQ has only a couple dozen data, so using occupation as a proxy for IQ allows me to cite a single data-set with over 1000 people! Given a 0.7 correlation between IQ and occupation (Jensen 1998) and assuming the brain-size vs occupation correlation is entirely caused by the brain-size vs IQ correlation, then a 0.25 correlation between occupation and brain size implies a 0.36 correlation between IQ and brain size (0.25/0.7).
In addition, a study by Susanne (1979) found a 0.19 correlation between head perimeter and Matrices IQ in 2,071 Belgian male conscripts. Given that matrices are only about 89% as g loaded as Wechsler IQ scales, and assuming the head size vs IQ correlation is mediated by g, it’s reasonable to divided 0.19 by 0.89 to estimate the correlation would have been 0.21 had the conscripts been given a gold standard IQ test like WAIS. Further, given that the head-size vs IQ correlation is likely virtually entirely caused by the brain-size vs IQ correlation, the fact that head circumference correlates about 0.60 with MRI brain volume (Rushton & Ankney 2007) means that if the conscripts had their brain sizes measured directly, instead of by head perimiter, the correlation would have jumped further to 0.35 (0.21/0.6).
So two massive data sets on adults both agree that the correlation between brain size and IQ is about 0.35. Further, I have shown that even the anomalously low 2015 meta-analysis would have likely yielded a correlation of 0.35 had range restriction been corrected for. Thus, 0.35 is very likely to be the true correlation between IQ and brain size among (white) adults in Western countries when either sex or body-size is controlled. Jensen and Rushton’s finding of 0.4 was likely not nearly the overestimate as we have been led to believe.
notice jensen isn’t wearing an undershirt.
and notice his not very big and ugly shaped head.
a TOTAL prole. just like murray.
and the narrow shoulders.
What does this have to do with the article?
http://pss.sagepub.com/content/early/2015/12/14/0956797615612727.abstract
What do you think about this meta-analysis which disproves any existence of a G x SES effect on IQ?
http://ericturkheimer.blogspot.ca/2015/12/the-tucker-drob-bates-meta-analysis.html
Turkheimer’s reply. He seems to agree that this is the death knell of the G x SES notion. Where does that leave us in regards to environmental effects on IQ? We just have lead and iodine deficiency.
The paper / meta-analysis I linked shows that when education is egalitarian, like in Europe, genes predominant in explaining variance. So it doesn’t matter.
Same with other complex traits. Hsu brings up height for example, no SES interactins.
I remember, once, a few years ago, when I had to take my son to a neurologist, to be examined for some seizures he had recently experienced. The doctor seemed to be impressed by my, then two-year-old, son, because of his vocabulary. The doctor said that he was a bright boy and that it made sense that he was, because he had a big head. He made a similar remark about both my intellect and head-size. It is funny how some people in the media and academy will deny the correlation of anything with intelligence, when all the while it is common knowledge to those who work in the field. Thankfully, the doctor determined that my son’s seizures were febrile in nature and not due to some defect in the makeup of his brain. All of my children have huge (but thankfully still normal looking) heads. However, for the life of me, I cannot recall exactly how large they were at birth. They seemed normal-sized at birth. I should look up their records to see how much growth they experienced during that first nine months.
compare the fairly robust bill clinton:
http://cmsimg.thejournalnews.com/apps/pbcsi.dll/bilde?Site=BH&Date=20080412&Category=LIFESTYLE01&ArtNo=804120306&Ref=AR&MaxW=640&Border=0&The-Clinton-workout
nixon has a great head shape. the forebrain is emphasized:
the same is true of kasparov:
it’s even true of the smartest dog breed:
You should look for people with a full head of hair.
At least you now accept intelligence is biological in nature.
environment affects biology.
and i’ve never denied, nor ever would deny, that there is some environment independent effect of genes on some reasonable interpretation of “intelligence”.
i’ve just denied that the evidence so far adduced is not anywhere near dispositive for the hereditsist case.
the dispositive study is un-ethical and im-possible:
MZ twins carried by randomly assigned gestational surrogates and raised by randomly assigned parents.
and by “randomly assigned” is meant:
randomly assigned either:
1. within the developed world
OR
2. within the entire world
AND NOT
3. within one country, (let alone) state, county, or city.
all behavior genetics studies must be criticized in this light. that is, to what extent do they conform to this gold standard?
a full head of hair?
no!
nixon and kasparov both still have some hair…but also have HUGE foreheads…
HUGE foreheads…
the term “highbrow” isn’t just a stereotype.
Hippocampal volume may have even less of a correlation than between head size and cortical volume. Mice who get human genes for hippocampal function perform way better. They are called super mice. The mouse brain is way small. Just try finding brain size correlations between the same species and their intelligence. This is why memory is so important because of how it is used. Some people may have genes that allow efficient signal processing without increase in size. Since memory is crystallized intelligence and fluid intelligence is the structure of the network to control and manipulate memory a large hippocampus will let you store more but a good network structure will allow better manipulation. Language is a different kind of fluid intelligence than perceptual. Between them the structure may connect or disconnect. Thus lower or raise manipulation. Multiple intelligence is really the interface between structures. The human brain is 80% efficient is its overall structure on average for integration. I do not remeber the study but I remember the numbers. Integration is why (g) cannot have a perfect test. The hippocampus will likely interface with those structures which lead to the diversity of cognition we seen in the population. White with IQ of 76 function less well than Africans with IQ 76. That is because as for what I have said may be because the network for europe adaption may be different than the network needed to adapt to africa. I suspect that africans have a much better hippocampal structure than whites to understand africa well whites had such warfare like systems that tools for them and the seasons meant that without continuous change they degenerate (as with IQ 76) well africans can sustain awareness that is more about being aware and in the present. They can remember the beautiful sunsets and the entirety of nature without frequent stress. War makes you stress out and shrink the hippocampus. This is why Plato did not like how writing was replacing the oral tradition. Outsourcing can destroy wisdom. Isolation happen more when you study one thing over another. An elephant never forgets. And they love their family. And they like to paint.
INTELLIGENCE NETWORK IN THE HUMAN BRAIN DISCOVERED
http://neurosciencenews.com/gene-clusters-intelligence-3299/
“Crucially, the scientists have discovered that these two networks – which each contain hundreds of genes – are likely to be under the control of master regulator switches. The researchers are now keen to identify these switches and explore whether it might be feasible to manipulate them. The research is at a very early stage, but the scientists would ultimately like to investigate whether it is possible to use this knowledge of gene networks to boost cognitive function.”
“Called M1 and M3, these so-called gene networks appear to influence cognitive function – which includes memory, attention, processing speed and reasoning.”
peepee’s simply dividing rho(y,z) by rho(x,z) to get rho(x,y) works if and only if
y = cx + a vector w such that w is orthogonal to both z and x.
of course if she’s getting her math lessons from a psychologist they’re going to be wrong 99% of the time.
I got this particular math lesson from Jensen. He was trying to estimate the g loadings of different IQ tests. He noted that since the correlation between two tests is the product of their factor loadings, then taking the square root of the correlation between two IQ tests gives the average g loading of the tests.
He noted that this would be an overestimate if the two tests had factors other than g in common, but felt that since the Picture Vocabulary test and Raven test have apparently nothing in common but g, then the square root of their 0.65 correlation tells you the average g loading of both tests: About 0.8.
It’s just an incredibly convenient little shortcut I like to use, but I agree it should be used with caution.
He noted that since the correlation between two tests is the product of their factor loadings…
this itself is only true if you design the factors that way, or jensen was using “factor” in a more specialized sense.
in general factors are just vectors in “subtest space” that aren’t themselves vectors of subtest scores but have small angles between themselves and some subset of the subtest vectors.
the axes of subtest space are individual scores. to each subtest there is a vector of scores of length N (= number of individual scores).
factors are thus not uniquely determined.
then the g “factor” for 2 vectors would be a bisector, but for 12 vectors what would it be? it could also be defined as the first principal component, and that is unambiguous.
this would mean that head size is determined by
1. brain size
2. other factors none of which have any relationship with either IQ or brain size.
is 2. a reasonable assumption?
I think 2 is reasonable enough. The other factors that determine head size might have some correlation with IQ and or brain size, but it’s probably small enough to be ignored in this kind of rough analysis.
I’ve lost all interest in science. Its run by frauds and cowards. Stephen J. Gould should have his grave robbed and the body dumped into a landfill for his fraudulent career. Tell your kids to skip college and learn a trade. If sociology and anthropology are science, then so are Astrology and Voodoo.
Both of those fields are as far from actual science as one can possibly get.
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