Questions on _g_ and intelligence

[Moonbear]

You give a lot of people a lot of different IQ tests. You take all the scores, by person, test, and question number, and do a statistical procedure called factor analysis, trying to find which combination of questions reduces the most variance on the data. This is like a regression, only more so. The result will be a set of subsets of questions, ordered by effectiveness in reducung variance. The top candidate is called the first principal component. You then identify the questions and convert their scores to a number. Spearman's g is this number for the first principal component of just about every IQ test and surrogate ever invented. It is enormously stable and correlated with things like the SAT, the Armed Forces tests, and so on. It also has physical correlates like measured reaction time and volume of gray matter in the prefrontal cortex.

Thank you so much for taking time to answer my questions! This is so much clearer to me. So, can any conclusions be drawn from the subset of questions that is used to compute the score for g? Do they have in common requiring a particular type of ability? As possible examples, spatial relations, verbal skills, analytical skills, forming associations between two different concepts, memorization tasks. The reason I'm asking is that now that I understand what g is, I'm wondering what about it makes it stable. Perhaps certain mental abilities are more important to survival on a more basic level, so are better conserved, whereas others are a "luxury" for those who have time to ponder the day away, so more variable? For example, key skills to surival...finding and remembering the places where food is, remembering which things made you sick so aren't good food, and remembering how to get from where you are to those places where the food are. So, basically, some memorization tasks and some spatial relations tasks. You don't need to know how to count to know if your belly is full, you don't have to add or subtract or multiply, you don't have to know a lot of words, though some basic communication to tell your family members where to find the food would be good, but you would need to make associations between different events...ate the green berries and later got a tummy ache, so green berries aren't good food. When it comes to solving problems that ask you to make analogies or find synonyms to words no normal person uses in every day conversation, I'd expect a lot more variation in ability simply because there is no real need for this skill.

 

[Mandrake]

Originally Posted by Mandrake
Do you mean her "kangaroo" link? I had seen that one before. It was put up by Steve Kangas, who says on his page that he is a student seeking a degree in Russian Studies. Is that a good source of scientific information? He identifies himself as an ultra-liberal and obviously has a very strong political agenda. If you look at his references, you will see that they include these scientific sources:
The San Francisco Chronicle
People For The American Way
USA Today
Boston Globe
The New York Times Magazine
Discovery Journal
The Nation,
Rolling Stone
Newsday
Newsweek.

Evo: You intentionally omitted all of the references from the American Psychological Association and the Human Genome Project.

You noticed? Maybe you thought my comment about "scientific sources" was serious? Guess not. Let me explain it to you ... I was making fun of the outrageous sources that were listed. I do not object to the use of a source that may have some scientific merits. Guess the subtlety was a bit too much for you.

How do you expect anyone to believe anything you say when you try to deceive them?

I made the horrible mistake of thinking that readers could understand what I wrote. You didn't.

If you have nothing to hide, why do you intentionally skew this list? Here are the sources Mandrake left out. I am disappointed in you Mandrake, I thought we could start over and debate this reasonably. Since you had to pick the other references from around them, you went to a deal of trouble to omit them.

A little testy today? I am sorry I made fun of the newspaper sources that you apparently believe are vehicles for serious science.

3. Tori DeAngelis, "Psychologists question findings of Bell Curve," APA Monitor, American Psychological Association, October, 1995.

This person identifies herself as a "writer." She does write about subjects that pertain to intelligence. So does the guy who is majoring in Russian Studies (Kangas). Does this person have any real credentials? The problem with the references you and others have produced is that they are precisely from the uninformed groups who have an ax to grind, but who are ignorant of the reliant science.

5. "APA Task Force Examines the Knowns and Unknowns of Intelligence," American Psychological Association, Press Release, September 15, 1995.

I have read this. I assume you have read it. What parts support your claims that The Bell Curve is invalid and that its authors are racists? Do you believe that the entire group of practicing psychometricians are evil racists? If so, does that go all the way back to Spearman?

11. Lori B. Andrews, Dorothy Nelkin and endorsing members of the Human Genome Project, "The Bell Curve: A Statement," letter to the editor, Science, January 5, 1996.

What expertise do you ascribe to a sociologist and a lawyer? These people are not experts in the field of psychometrics, nor have they published research findings in psychometrics. They are simply critics, who fit the mold of your newspaper and Russian Studies experts. Why are you so attracted to people who have little commitment to the study of intelligence, while holding in contempt the scientists who have devoted their entire careers to it? When you are ill, do you hold physicians in contempt and seek help from a newspaper?

Originally Posted by Mandrake
APA is not a group of psychometricians, it is a group of psychologists, a few of whom may be psychometricians.

Evo: You seem to think quite highly of psychometricians, when I have sometimes heard "psychometrics" referred to as "voodoometrics", which I think isn't nice since there are good people and bad people and I disagree with labeling groups of people, it isn't right or completely true.

If we were discussing astronomy, would you think it appropriate to take expert commentary from astronomers, or lawyers? If we were discussing insects, would you want to be quoting an entomologist, or someone who describes himself as an admirer of Russians and an ultra liberal?

Originally Posted by Mandrake
When a letter goes out, it is not the joint finding of the entire membership nor is it the joint finding of those members who are actually qualified to make a judgement.
Evo: Which is exactly why the APA formed an unbiased committee , including Thomas Bouchard. You can't get much more pro Bell Curve than that.

The APA report addresses some issues quite well; it addresses others incompletely; and it misrepresents some issues. Consider the discussion about heritability. They discuss only MZA data and say nothing about path analysis. Why? The results are in agreement, but the literature claims are that path analysis is more robust. In this area, they had no way of knowing what would later be discovered by Dr. Paul Thompson at UCLA: "We were stunned to see that the amount of gray matter in frontal brain regions was strongly inherited, and also predicted an individual's IQ score..." His work was done with MRI. Their coverage of the Scarr-Weinberg findings was poor.

 

[Mandrake]

Since you (Evo) place a lot of weight on the people who served on the task force, I would like to make observations about some of them, supplemented by some of their material:

Ulric Neisser, Emory University (chair of the task force)
A real psychometrician. His interest has been in the Flynn Effect.

Thomas J. Bouchard, Jr., University of Minnesota

The scientific study of general intelligence: Tribute to Arthur R. Jensen
H. Nyborg (Ed.), 2003, Elsevier, Oxford, UK, ISBN0080437931
Thomas J. Bouchard:
This is a gem of a book and a fitting honor to a distinguished scientist and scholar.
Arthur Jensen has single-handedly reinvigorated the scientific study of human intelligence and his magnum opus—The g Factor: The Science of Mental Ability (Jensen, 1998) (henceforth, SMA)—will remain a definitive work for many years to come. As Jensen has shown, g lies at the nexus of a large set of causal empirical relationships that encompass every aspect of human life, from birth to death. This nexus links psychology to biology, genetics, neuroscience, sociology, demography, the humanities, and the arts. There is an emerging discipline called the Epidemiology of Human Intelligence. The book under review follows the Bell Curve (Herrnstein & Murray, 1994) and SMA in helping lay the foundations of that discipline.

Description versus strong inference --Thomas J. Bouchard Jr.
Intelligence, Volume 29, Issue 2 , March-April 2001, Pages 187-188
Since Scarr (1997) has shown quantitatively that socialization effects, found in studies of biological families, are confounded and almost all such effects can be explained by genetic factors, adoption controls are mandatory. Hand waving away the competing genetic hypothesis simply will not do.

A. Wade Boykin, Howard University
His interest seem to be restricted to blacks. He even wrote instructions for black psychologists, as if the skin color of a psychologist requires a different set of research instructions.

Nathan Brody, Wesleyan University

Here are a few of his comments from Kings of Men: Introduction to a Special Issue of the Journal of INTELLIGENCE (1998)

I believe that anyone who wishes to write about the issue of race and intelligence must acknowledge Jensen's formidable contributions to this topic and his comprehensive knowledge of this area of research. Jensen's book on bias in testing is an extraordinarily thorough and scholarly analysis of the issue of test bias (Jensen, 1980). I like to compare this book with another book that I admire greatly, Paul Meehl's monograph on Statistical vs. Clinical Prediction (Meehl, 1954). Both books serve to define the principal issues that must be understood in addressing the topics that they consider. Both books develop their arguments with unusual clarity and sophistication. And, to a remarkable extent, the conclusions reached in both books have stood the test of time and become part of the canon of empirically established generalizations that define our knowledge of important topics. Jensen established what is now close to the received wisdom of knowledgeable students of intelligence -- tests of intelligence are equally valid indices of the performance of individuals who differ with respect to their racial identification. In several technical senses of the term, they are not biased -- a conclusion endorsed in the recently published report of the American Psychological Association's task-force on intelligence composed of individuals with diverse views of the field (Neisser et al., 1996).

Jensen is not an ideologue or a person who is not able to respond to criticism in a fair way. He is a scientist with formidable technical skills who strives for an understanding of the topics that he addresses. In this regard, his work is a model of scientific decorum. We should all strive to emulate his ability to test our beliefs against a recalcitrant reality that often is resistant to our ability to represent it in distorted ways. In the long run, if we are clever and honest, it will impose its structure and truth on us rather than ours on it.

In my opinion, Jensen's most important contribution to the field is contained in his new book on the g factor (Jensen, 1998). In the first paper dealing with g, Spearman attempted to determine the g loadings of different measures of intelligence (Spearman, 1904).

Jensen (1998) links the g vector to several biologically relevant vectors. He notes that Pedersen et al. (1992) obtained heritability values for different tests in a battery of tests of intelligence administered to a sample of older Swedish adult MZ and DZ twins reared together and apart. The vector defining the heritability of the tests is correlated with the vector defining the independently ascertained g loadings, r = .77. Jensen provides additional evidence based on Wechsler sub-test g loadings indicating that the vector of g loadings is correlated with the vector of heritability values for Wechsler sub-tests.

Jensen's analyses of the correlates of g vectors provide the quantitative underpinning for what has long been apparent -- g is a biologically influenced heritable component of the commonality among diverse measures of intellect that is related to the ability of individuals to acquire knowledge in formal academic contexts. Perhaps we have always known this, but following Jensen's highly original use of analyses of the correlates of g vectors we know this with a kind of quantitative precision not heretofore available.

Jensen's work on the correlates of the g vector reveals some of his best attributes -- an ingenious ability to develop quantitative analyses that address fundamental issues in highly original ways that advance our knowledge of critical issues in the field.

Stephen J. Ceci, Cornell University
Focus is on children. His positions on many issues are in conflict with real world findings.

Diane F. Halpern, California State University, San Bernadino
Her work is in the area of family issues and children, not psychometrics.

John C. Loehlin, University of Texas, Austin

His comments pertaining to the Texas Adoption Project from Intelligence, Volume 24, Issue 2 , 1997, Pages 323-328

The children have so far been studied twice-once at the time of the initial study, when they averaged about 8 years old (although spanning a range of ages), and again, roughly ten years later, when most of them were late adolescents or young adults. The results with regard to IQ were straightforward enough to delight even a Willer-man. The adoptive childtens’ IQs resembled those of their birth mothers, whom they had never seen, more than they did those of their adoptive mothers, with whom they had lived all their lives. Biologically unrelated children reared as siblings (pairs of adopted children in the same home, or an adopted and a biological child) resembled one another to some degree at the time of the first testing, when they were still children, but by the time of the second testing, when most of them were late adolescents or young adults, these cormlations had dropped essentially to zero. That is, children who grew up together but who did not share a genetic resemblance were somewhat similar in their measured IQs when they were young, but by late adolescence their genetic differences had expressed themselves, and they were as different as any two randomly-selected members of the (somewhat restricted) population to which they belonged.


Robert Perloff, University of Pittsburgh
Professor of Business Administration. Expert? :-)

Robert J. Sternberg, Yale University

I have discussed Sternberg here before. He advocates his Triarchic Theory, which does not stand up to scrutiny, as has been demonstrated dramatically by Linda Gottfredson.

Originally Posted by Mandrake
At this point, the only people doubting the 100 year study of the variance in intelligence are crackpots.
Evo: So, you claim the people listed above are crackpots? Nice.

Evo, your personal contempt has replaced rational thought. Do you seriously think that the people in question doubt the variance in intelligence that has been demonstrated over the past century? Try reading some of the comments they made, which I quoted. You really don't get it do you?

Here is another link on The Bell Curve from the University of Wisconsin.

Did you read this article? If so, what are your thoughts about it? Just posting a link by two economists doesn't add much to the discussion. Is there some reason why you consider that psychometrics is a subcategory of economics? My reading of the paper showed that the authors used approaches that appear to be reasonable, but which, as usual, ignore the details of what is known about the subject. This is apparent in their discussion of heritability. What are your deepest and most profound thoughts on this paper? Oh, I forgot to ask, did you read it before posting the link??

 

[Mandrake]

Dorothy Nelkin, Professor of Sociology, member of the Human Genome Project, here are some of her publications, these just from 1990-1995

I had already looked and found that these women had no background in psychometrics. Sorry to inform you, but the areas addressed by their publications (however important they may be for other purposes) are not sufficient to qualify them to address psychometric issues with authority. It remains amazing to me to see how important it is to you to show us all that there are people in various other fields who don't understand psychometrics, but who say what you want to hear.

 

[Moonbear]

Of these, the brain volume subject has received particularly prolonged study. The development of fMIR technology has enabled researchers to identify and measure the volumes of specific parts of the brain and to correlate them to _g_ (even group factors show up as specific locations). The research was done by Richard Haier and was presented at the 2003 ISIR conference. This is cutting edge material.

As promised, I'm trying to get back to this topic when less tired...and now I also have a better idea of what "g" is, so that helps.

It occurs to me that my initial confusion on this is that my interpretation of "specific" brain regions is probably different from what you meant. Using MRI, you can measure gross brain structures that have clearly defined boundaries, such as cortex, cerebellum, hippocampus, corpus callosum. You can also use methodologies that tell you what areas are "activated" during certain tasks by measuring changes in blood flow or glucose uptake, but these sorts of analyses are often open to varied interpretations (even in less controversial areas than intelligence), and it doesn't reflect the size of that brain area, just the part of it that is being used. The two general interpretations that can be taken when there is a group difference in the size of an area that "lights up" on an MRI is that either there is more activity, so a greater ability to use that region in that group, vs the group that shows less activity may be more efficient in processing of that task, so uses only a smaller area of the brain. The other controversy is whether blood flow and glucose uptake really translate into actual function. But for now, people are generally willing to accept that this is the case, and that controversy is more a nuance of the field. When I think of "specific" brain areas, I'm thinking of specific nuclei within a region. For example, in MRI, you can measure the volume or thickness of cortex in a given slice, and you could use some other landmarks to identify, for example, prefrontal cortex (I picked that because it's an area SelfAdjoint mentioned as correlating to g), but, within prefrontal cortex, there are multiple nuclei such as the infralimbic nucleus and prelimbic nucleus. These different nuclei contain a variety of different neuronal subtypes that differ between the nuclei both in neurotransmitters and receptors as well as functions...you get a very different neurological/behavioral outcome if different nuclei are lesioned, for example. And a variety of functions are attributed to this area, including things like working memory, impulse control, addiction, sexual behavior, some better described in the literature than others. I'm not sure if an MRI scan would really pick up differences associated with just parts of the PFC. And saying something is correlated to a change in the size of the PFC doesn't mean a lot to me...I would want to know which nucleus? Which cells in the nucleus? If someone had a deficit in the area related to working memory, that would certainly explain a lower test score, however, deficits in other areas might also lead to problems with taking tests that isn't related so much to intelligence as to just staying focused on the test.

The point of my comment is that these differences appear as group differences and correlate with _g_ independently of the group identity. For example, that means that the mean brain volume differences between US blacks and US whites are as expected, given the differences in mean IQs for these two groups. Chronometric measurements similarly vary between groups in proportion to the observed differences in _g_ between the groups.

I just found this fascinating article. It does show a clear relationship between IQ and head circumference, though they focus on the extremes, where head circumference was at or below 2 SD from the mean. The main conclusion is that head circumference and brain volume are related to IQ, and that this smaller head circumference and brain volume are strongly related to early childhood malnutrition. In this study, they were assessing adults, but the correlation to malnutrition is based on their earlier work that they also cite. There is also a really interesting paragraph in the introduction that explains that comparisons between racial groups are not valid, even when using height and weight to correct for head circumference variations, because height and weight are not unformly covariate with head circumference. Here is the citation and some excerpts (my editing for clarity is in red text).

Neuropsychologia 42 (2004) 1118–1131
Head size and intelligence, learning, nutritional status and brain development Head, IQ, learning, nutrition and brain
Daniza M. Ivanovic, Boris P. Leiva, Hernán T. Pérez, Manuel G. Olivares, Nora S. D´?az , Mar´?a Soledad C. Urrutia, Atilio F. Almagià, Triana D. Toro, Patricio T. Miller, Enrique O. Bosch, Cristián G. Larra´?n

To view the full article, go to: http://dx.doi.org and in the text box, enter:
doi:10.1016/j.neuropsychologia.2003.11.022

Abstract
This multifactorial study investigates the interrelationships between head circumference (HC) and intellectual quotient (IQ), learning,
nutritional status and brain development in Chilean school-age children graduating from high school, of both sexes and with high and low
IQ and socio-economic strata (SES). The sample consisted of 96 right-handed healthy students (mean age 18.0 ± 0.9 years) born at term.
HC was measured both in the children and their parents and was expressed as Z-score (Z-HC). In children, IQ was determined by means
of theWechsler Intelligence Scale for Adults-Revised (WAIS-R), scholastic achievement (SA) through the standard Spanish language and
mathematics tests and the academic aptitude test (AAT) score, nutritional status was assessed through anthropometric indicators, brain
development was determined by magnetic resonance imaging (MRI) and SES applying the Graffar modified method. Results showed that
microcephalic children (Z-HC ? 2S.D.) had significantly lower values mainly for brain volume (BV), parental Z-HC, IQ, SA, AAT, birth
length (BL) and a significantly higher incidence of undernutrition in the first year of life compared with their macrocephalic peers (Z-HC >
2 S.D.). Multiple regression analysis revealed that BV, parental Z-HC and BL were the independent variables with the greatest explanatory
power for child’s Z-HC variance (r2 = 0.727). These findings confirm the hypothesis formulated in this study: (1) independently of age,
sex and SES, brain parameters, parental HC and prenatal nutritional indicators are the most important independent variables that determine
HC and (2) microcephalic children present multiple disorders not only related to BV but also to IQ, SA and nutritional background.

Some authors emphasise that, at present, there is no
meaningful basis for the comparison of brain sizes within
and between racial groups and sexes; the control for body
size across racial groups (and sexes) is rendered difficult
because bodies do not just differ only in H(Height) and W (Weight)(Peters
et al., 1998). In the present study, the correlations between
BV (Brain Volume)and H and W were very low, as we informed in a
previous report (Ivanovic et al., 2002) and the analysis of
covariance (Guilford & Fruchter, 1984) revealed that no
significant effect of sex, H and W was observed for BV;
however, despite of this, values were adjusted by body size
(W and H) but were so similar to absolute values that only
these are reported in the present study.

HC (Head Circumference) has been recognised as the most
sensitive anthropometric index of prolonged undernutrition
during infancy, associated with intellectual impairment especially
verbal IQ, such as in our study (Ivanovic et al.,
2000d; Leiva et al., 2001; Stoch et al., 1982). Undernutrition
was significantly more prevalent in children with a low HC
(<?2 S.D.) who presented the lowest verbal IQ, BV (Brain Volume) and
APD (Anterior-Posterior Distance of the brain) values and this latter finding is especially outstanding
since APD involves language and visualisation areas (Stoch
et al., 1982; Willerman et al., 1991); this could explain that
in children with low HC (<?2 S.D.), verbal skills are more
deteriorated than non-verbal skills (Ivanovic et al., 2000d;
Stoch et al., 1982). In children with HC >2 S.D., verbal IQ
was higher than nonverbal IQ and in groups with a “normal
HC “ (mean±2 S.D.) similar values were found between total,
verbal and non-verbal IQ although IQ was significantly
higher in 0–2 S.D. group. Findings from several studies
emphasise that among preschoolers HC might reflect better
than body H the impact of nutritional deficiencies at an
early age; this measurement is useful in the identification of
the period during which malnutrition occurred (Johnston &
Lampl, 1984; Malina et al., 1975).

It has been suggested that individual differences
in myelination, which affects neural transmission
rates, may be the basis for the HC–BV–IQ correlation although
there is a low correlation between neural speed and
mental speed, suggesting that other mechanisms must be involved
(Miller, 1994; Tan, 1996; Vargas et al., 2000;Wickett
& Vernon, 1994). Delayed myelination and abnormalities in
neuron migration have been described as the most predominant
disorders in children with associated neurologic findings...

 

[Evo]

You noticed? Maybe you thought my comment about "scientific sources" was serious? Guess not. Let me explain it to you ... I was making fun of the outrageous sources that were listed. I do not object to the use of a source that may have some scientific merits. Guess the subtlety was a bit too much for you

A little testy today? I am sorry I made fun of the newspaper sources that you apparently believe are vehicles for serious science..

They are references to where certain quotes and other information came from, they aren't supposed to be scientific references. I thought that was obvious, I guess not.

I will respond to the rest later when I have more time, it might be tomorrow.

 

[Evo]

I had already looked and found that these women had no background in psychometrics. Sorry to inform you, but the areas addressed by their publications (however important they may be for other purposes) are not sufficient to qualify them to address psychometric issues with authority. It remains amazing to me to see how important it is to you to show us all that there are people in various other fields who don't understand psychometrics, but who say what you want to hear.

Like it or not Mandrake, those two are extremely qualified. I notice that you tend to dismiss and even skip over anyone or anything that disagrees with you, as in your list of the APA panel. If you agree with them, you praise them to the heavens and post comments of theirs that make you happy, if you don't agree with them, you post nothing of what they say and skip over them. You are so funny and predictable.

 

[Moonbear]

I've run out of characters in my above post to edit it...those strange apostrophe's followed by question marks in the authors names are supposed to be the letter i with an accent. For some reason, the characters didn't display correctly.

 

[Evo]

I just found this fascinating article.

Well, I was going to get some work done, but your post and this article are too interesting.

I went to read the rest of the article and I can't. I don't have a password.

 

[hitssquad]

What types of abilities are characteristic of g

can any conclusions be drawn from the subset of questions that is used to compute the score for g? Do they have in common requiring a particular type of ability? As possible examples, spatial relations, verbal skills, analytical skills, forming associations between two different concepts, memorization tasks.

• High g Loading
  Matrix relations (.94)
  Generalizations (.89)
  Series completion (.87)
  Verbal analogies (.83)
  Likeness relations (.77)
  Problem arithmetic (.77)
  Paragraph comprehension (.73)
  Perceptual analogies (.70)
  
  
• Low g Loading
  Maze speed (.04)
  Crossing out numbers (.12)
  Counting groups of dots (.14)
  Simple addition (.23)
  Tapping speed (.24)
  Dotting speed (.27)
  Paired-associates memory (.27)
  Recognition memory (.31)

(Arthur Jensen. The g Factor. p35.)

Do they have in common requiring a particular type of ability?

• Spearman concluded that the tests that best reflect g are those that most involve the "eduction of relations and correlates." These are the tests that require inductive and deductive reasoning, grasping relationships, inferring rules, generalizing, seeing the similarity in things that differ (e.g., reward-punishment) or the difference between things that are similar (love-affection), problem solving, decontextualizing a problem (that is, distinguishing between its general, or essential, features and its specific, or nonessential, features). These all manifest the second and third "laws" of noegenesis--the eduction of relations and of correlates. They are contrasted with tests that call mainly upon speed of execution of simple tasks, performance of repetitious acts, simple cued recall of prior learned responses, execution of a practiced sequence or chain of responses, and direct imitation of another person's specific action without conscious transformation.

(Ibid. pp35-36.)


However:

• Unlike group factors, g cannot be described in terms of the superficial characteristics or information content of the tests in which it is loaded. All mental tests have some degree of g loading and even extremely dissimilar tests (e.g., sentence completion and block designs) can have nearly equal g loadings. Group factors, on the other hand, are labeled and described in terms of the obvious characteristics of the kinds of tests that load on them (such as verbal, numerical, spatial visualization, memory, mechanical, to name a few of the established group factors).
  
  Further, g is not describable in terms of any pure or unique behavior... There is no single distinct type or class of behavior or materials required for the manifestation of g... The fact that a certain class of tests measures g more efficiently than other tests does not qualify the characteristics of the former tests to be considered the "essence" or "defining characteristics" of g.

(Ibid. pp91-92.)

• The Confusion of g with Mental Processes. It is important to understand that g is not a mental or cognitive process or one of the operating principles of the mind, such as perception, learning, or memory... ...g only reflects some part of the individual differences in mental abilities...

(Ibid. p95.)

• The knowledge and skills tapped by mental test performance merely provide a vehicle for the measurement of g. Therefore, we cannot begin to fathom the causal underpinning of g merely by examining the most highly g-loaded psychometric tests.

(Ibid. p74.)

When it comes to solving problems that ask you to make analogies or find synonyms to words no normal person uses in every day conversation, I'd expect a lot more variation in ability simply because there is no real need for this skill.

A skill is not an ability. Skills result from practice, whereas abilities are inherent. However, higher ability results in faster and ultimately greater skill gain from any given amount of practice. This is why skill testing can indirectly indicate ability level.

As far as "no real need for" abilities that are characteristically highly g-loaded, every human activity is g-loaded to some extent, and persons with higher levels of g perform these activities more proficiently:

• The effects of g encompass a broader range of uniquely human phenomena than any other psychological construct... Applied research has concentrated on the importance of g in education, employment, economic development, health, welfare dependency, and crime.

(Ibid. p545.)

 

[Moonbear]

Well, I was going to get some work done, but your post and this article are too interesting.

I went to read the rest of the article and I can't. I don't have a password.

Well, at least I won't have to feel bad about keeping you from doing your work. Sorry about that. I thought that link I provided got me there without going through my university library...I guess it still knew

 

[Moonbear]

Hitsquad, all the information you've provided today is incredibly helpful! I feel I have a much better grasp of this subject now. Actually, a lot of what you included in this last post (#45) makes a lot of intuitive sense about what I've noticed in terms of my students and how well they learn.

Despite what an old professor once told me (he was quite fond of Piaget), I've found that students can be taught to make and understand relationships between things (that old prof told me they just reach that developmental stage on their own and some never do). The ability to identify relationships, especially complex relationships, really seems to reflect a student's likelihood of success, certainly as a scientist (there comes a point where rote memorization just doesn't carry you any further). So, it seems from what you're saying about g, is that it's sort of halfway between my views and my old prof's views. Students probably all possesses the ability to identify those relationships among concepts, but some are slower than others to develop it and express the skill, and with some coaching, I can help them develop that ability into actual skill.

What you've posted isn't nearly so bleak sounding as the way I've seen it interpreted in other threads. Others seem to suggest (or maybe it was my misunderstanding of what they were saying) that if someone has a low g score, then they have no hope of doing what those with a high g score can do, but instead, it may just take them a little more time to get there. Well, that makes sense. We all know there are slow learners and fast learners. Sure, there are some people who have a developmental defect who just lack the brain cells to ever perform beyond a certain level, but I like to be an optimist and think that those within that broad range of "normal" are all equally capable of achieving the same thing, though those at one end of that normal spectrum may take a little longer than those at the other end.

 

[hitssquad]

The teaching and shape of the population distribution of g

I feel I have a much better grasp of this subject now.

In that case, you probably have a looser grasp.

I've found that students can be taught to make and understand relationships between things

Oppositely, research has never been able to demonstrate any rise in g following intellectual exercise.

The ability to identify relationships

g is not an ability.

Students probably all possesses the ability

g is not an ability.

to identify those relationships among concepts, but some are slower than others to develop it and express the skill

Identification of novel relationships does not demonstrate skill. If it did, identification of novel relationships could be taught and learned.

and with some coaching, I can help them develop that ability into actual skill.

No one has ever been able to successfully coach rises in g under controlled, documentable conditions.

Others seem to suggest that if someone has a low g score, then they have no hope of doing what those with a high g score can do

Someone with any given reliably-attained g score has no hope of successfully executing any task with a g threshold above his measured level of g.

but instead, it may just take them a little more time to get there.

No.

Sure, there are some people who have a developmental defect who just lack the brain cells to ever perform beyond a certain level, but I like to be an optimist and think that those within that broad range of "normal" are all equally capable of achieving the same thing, though those at one end of that normal spectrum may take a little longer than those at the other end.

This is analogous to the pre-Newton conception of gravity as affecting ballistic objects only at certain critical points in their flight paths. IOW, it was once thought that ballistic objects fly in perfectly straight lines to the apexes of their flight paths, then, once there, suddenly start dropping straight down. Your IQ distribution would have all of the "middle" people at exactly IQ 100 and a few retardates at a given retardate level and a few gifteds at a given gifted level. No one would have an IQ of 110, and no one would have an IQ of 90.

Contrarily, research has demonstrated that:

• There are plausible reasons ... for assuming that individual differences in g have an approximately normal, or Gaussian ("bellshaped"), distribution, at least within the range of ±2σ from the mean. That range is equivalent to IQs from 70 to 130 on the typical IQ scale (i.e., μ = 100, σ = 15).

(Arthur Jensen. The g Factor. p88.)

I like to be an optimist and think that those within that broad range of "normal" are all equally capable of achieving the same thing

There has not been presented any reasoning why a possibility of massive equality in distribution of general mental ability should have any relationship with optimism.

 

[Mandrake]

So, can any conclusions be drawn from the subset of questions that is used to compute the score for g? Do they have in common requiring a particular type of ability?

When a test item requires thinking, it always calls on _g_. If a task has been learned to the point of automatic response, it is not calling on _g_ and is an example of a learned response. You can teach people to increase forward digit span, but in so doing, testing them on that ability is not as _g_ loaded as it would be if they were not trained. When they are then tested or reverse order digit span, they will not show that ability gains that were learned in forward recall.

As possible examples, spatial relations, verbal skills, analytical skills, forming associations between two different concepts, memorization tasks.

The items you listed are generally extracted at the second order of a factor analysis and are called group factors. Each of them is loaded on _g_, _s_, and _e_. The third order extraction yields _g_, which is the variance that is common to all of the group factors.

The reason I'm asking is that now that I understand what g is, I'm wondering what about it makes it stable.

_g_ is relatively stable over most of adult life and is so because it is rooted in physiology. I have previously listed the biological correlates of _g_. Such critical factors as nerve conduction velocity are biologically stable. The same applies to the degree of myelination. In old age, these may degrade and reduce intelligence. Some diseases may do the same thing. MS causes demyelination and causes IQ to decline.

 

[Mandrake]

Like it or not Mandrake, those two are extremely qualified.

I don't doubt that they are qualified in their fields. If you wanted to hire someone to represent you in a court of law, would you hire a psychometrician or a lawyer?

There is no requirement that a psychometrician hold a particular university degree. This is especially so because the field of psychometrics is quite removed from much of psychology and makes particularly heavy demands on statistical knowledge and laboratory research. The thing that distinguishes a psychometrician (or other specialist) is his devotion to the subject at hand, years of study, years of research, and participation in the publication of peer reviewed research. The women you listed are not qualified to peer review psychometric research.

I notice that you tend to dismiss and even skip over anyone or anything that disagrees with you, as in your list of the APA panel.

The APA group was selected for what appears to be political purposes. The APA is not a psychometric organization and as such, contains a lot of membership that is unqualified to deal with the subject. My observation is that you prefer comments from sources in proportion to their distance from the subject, wanting to believe only the things that originate from layman sources.

If you agree with them, you praise them to the heavens and post comments of theirs that make you happy, if you don't agree with them, you post nothing of what they say and skip over them.

If I know that the person is or is not qualified, I say so. You can always disregard my comments or call me a liar (as you have already done). That does not change my assessment. If I know nothing about the person, I cannot comment, can I?

You are so funny and predictable.

It is very kind of you to say so. This is an improvement over being called a racist and liar. I wonder if you interact with people in person with the same rudeness that I have seen in your messages?

I have a serious suggestion for you: Don't read my messages. For whatever reason, you cannot react to what I write in a civil way nor do you contribute positively to the ideas presented. As an alternative, simply read the comments by hitsquad. Read the recent ones he has posted in this thread in the past two days. Try to understand what he has presented and you will learn something useful about psychometrics. You are wasting your time being combative with me.

 

[Mandrake]

It occurs to me that my initial confusion on this is that my interpretation of "specific" brain regions is probably different from what you meant. Using MRI, you can measure gross brain structures that have clearly defined boundaries, such as cortex, cerebellum, hippocampus, corpus callosum.

Here is a piece of the report I previously mentioned:
Human Intelligence Determined By Volume And Location Of Gray Matter Tissue In Brain Source: University Of California - Irvine Date: 2004-07-20

The researchers used a technique called voxel-based morphometry to determine gray matter volume throughout the brain which they correlated to IQ scores. Study results appear on the online version of NeuroImage. Previous research had shown that larger brains are weakly related to higher IQ, but this study is the first to demonstrate that gray matter in specific regions in the brain is more related to IQ than is overall size. Multiple brain areas are related to IQ, the UCI and UNM researchers have found, and various combinations of these areas can similarly account for IQ scores. Therefore, it is likely that a person’s mental strengths and weaknesses depend in large part on the individual pattern of gray matter across his or her brain.

“This may be why one person is quite good at mathematics and not so good at spelling, and another person, with the same IQ, has the opposite pattern of abilities,” Haier said.

While gray matter amounts are vital to intelligence levels, the researchers were surprised to find that only about 6 percent of all the gray matter in the brain appears related to IQ.

“There is a constant cascade of information being processed in the entire brain, but intelligence seems related to an efficient use of relatively few structures, where the more gray matter the better,” Haier said. “In addition, these structures that are important for intelligence are also implicated in memory, attention and language.”

The research does not address why some people have more gray matter in some brain areas than other people, although previous research has shown the regional distribution of gray matter in humans is highly heritable. Haier and his colleagues are currently evaluating the MRI data to see if there are gender differences in IQ patterns.

I just found this fascinating article. It does show a clear relationship between IQ and head circumference, though they focus on the extremes, where head circumference was at or below 2 SD from the mean.

I haven't had a chance to read the article, but I wonder why anyone would still be looking at head circumference, when we have a means of measuring brain volume and now a means of measureing the volumes of those small parts of the brain that contribute to intelligence?

The subject of brain size versus IQ has been studied and reported so extensively that the only likely new information is going to come from new laboratory techniques, such as those being used by Richard Haier.

Some brain and head size related factoids:

The average female brain is smaller than the average male brain. This is true, even after the size difference is corrected for relative differences in body size. The average male brain is about 12.5% heavier.

The average female brain has more neurons per unit volume than the average male brain (about 11%).

The average brain and head size is smaller for blacks than for whites.

The number of neurons in the brain is fixed by age 4, but the brain size to intelligence correlation is weak at age 4. By age 7 there is a significant within family effect. Miller argues that this is consistent with his myelination hypothesis because myelination of the brain is not significant at age 4, but is much more so at 7 and continues through adolescence.

The correlation between body size and brain size in adults is between .20 and .25.

The correlation between head size and IQ ranges from .10 to .25 (various studies), with a mean of .15.

The correlation (one study only) between head size and _g_ is .30.

The correlation between brain size, as measured by MRI, and IQ is .40 (corrected for body size).

 

[Moonbear]

Here is a piece of the report I previously mentioned:
Human Intelligence Determined By Volume And Location Of Gray Matter Tissue In Brain Source: University Of California - Irvine Date: 2004-07-20

That's a news article, not a research article. But at least it mentions the names of one of the researchers (Haier), so I'll have to look up what they've published (sounds like it's available in NeuroImage, which I have access to).

I haven't had a chance to read the article, but I wonder why anyone would still be looking at head circumference, when we have a means of measuring brain volume and now a means of measureing the volumes of those small parts of the brain that contribute to intelligence?

They didn't just measure head circumference. They measured brain volume as well, and even broke it down further by size of some other brain regions. They used head circumference because it is an easy measure that is related to malnutrition during infancy and early childhood and were looking to see if it was a consistent predictor of brain volume and IQ.

Some brain and head size related factoids:

The average female brain is smaller than the average male brain. This is true, even after the size difference is corrected for relative differences in body size. The average male brain is about 12.5% heavier.

The average female brain has more neurons per unit volume than the average male brain (about 11%).

Much of this difference is well-established as relating to areas involved in sexual behavior, reproductive function, maternal behavior. Besides, the two facts you present together don't indicate any difference in neuronal number, just that the density of neurons is greater in women than men, so their brains are more compact. This is far too simplistic though, since there are some brain areas that are larger in women than men. It relates to gender-specific brain functions.

The average brain and head size is smaller for blacks than for whites.

Based on the article I cited above, this would indicate we should be seriously looking into the extent of malnutrition among the black population in the US, especially in pre-school aged children, since it seems nutritional interventions for school-aged children may be too late to help.

The number of neurons in the brain is fixed by age 4, but the brain size to intelligence correlation is weak at age 4. By age 7 there is a significant within family effect. Miller argues that this is consistent with his myelination hypothesis because myelination of the brain is not significant at age 4, but is much more so at 7 and continues through adolescence.

We now know that there is remarkable plasticity in both neuronal numbers and connections in adults. Adults still have neuronal stem cells capable of producing new neurons (this has only really come to light within probably the last 5 years or so). It used to be believed that once we hit adulthood, we could only lose brain cells, not grow new ones, but that has been completely overturned.

The myelination hypothesis seems to be in contradiction to the summary you posted of work by Haier's group, which stated that it was gray matter volume that is important to IQ. Gray matter is gray because it is unmyelinated. Though, white matter and gray matter are pretty archaic terms.

The correlation between body size and brain size in adults is between .20 and .25.

The correlation between head size and IQ ranges from .10 to .25 (various studies), with a mean of .15.

The correlation (one study only) between head size and _g_ is .30.

The correlation between brain size, as measured by MRI, and IQ is .40 (corrected for body size).

What statistic is being used for these correlations? I'm accustomed to correlations being reported as an r-value, where 0 is no correlation and 1 is a high correlation. Any correlation near 0.5 would be pretty equivocal, and something as close to zero as .1 or .2 would mean there is no correlation at all. In either case, correlation does not mean causation, it may mean both are affected by the same causational event, such as prolonged childhood malnutrition. In combination with the article on folate levels (the other thread of that topic) and IQ, this may all be attributable to a difference in metabolism that requires an even higher level of intake of certain nutritients than we are teaching the public is required for being healthy.

 

[Evo]

There is no requirement that a psychometrician hold a particular university degree. This is especially so because the field of psychometrics is quite removed from much of psychology and makes particularly heavy demands on statistical knowledge and laboratory research. The thing that distinguishes a psychometrician (or other specialist) is his devotion to the subject at hand, years of study, years of research, and participation in the publication of peer reviewed research. The women you listed are not qualified to peer review psychometric research.

So, regardless of a person's qualifications, you won't believe them unless they are a psychometrician, ok, here's a Ph.D. in Psychometrics.

Peter H. Schönemann, Professor Emeritus, Department of Psychological Sciences, Purdue University, Ph.D Illinois, 1964; General Psychology

Ph.D. in psychometrics at the UofI.

Studies the effect of genetics on human behavior. Says genetics play only a small role in intelligence and behavior. Teaches course about intelligence, or IQ, tests. Is opposed to using aptitude tests to predict future success of students.

Here are a few excerpts.

IQ Controversy

(a) Problem of defining "intelligence":

"In his controversial revival of the eugenic traditions of the 20s, Arthur Jensen (1969) appealed explicitly to Spearman's factor model as a vehicle for defining "intelligence". However, in view of the factor indetermincay problem (see above, factor analysis), these high hopes are doomed to failure [40, 47, 52, 57, 83] . Recourse to concrete IQ tests is equally unsatisfactory, because different tests are often quite poorly correlated. In fact , this was the reason why Spearman had postulated his factor model in the first place. From a purely pragmatic point of view one further finds that, contrary to what some authors who should know better have claimed, conventional IQ tests are surprisingly poor predictors of most criteria of practical interest, including scholastic achievement. For example, the SAT - a descendent of conventional "verbal" IQ tests such as the Army Alpha - consistently performs worse than easily available previous grades as a predictor of subsequent grades. This was known, though not advertised, since the 20s. For long range criteria (such as graduation or GPA at graduation), the SAT usually accounts for less than 5% of the criterion variance (Humphreys, 1967, Donlon, 1984). As one might expect, the picture dims further for the GRE: In two recent, large scale, validity studies, Horn and Hofer (undated) and Sternberg (1998 ) found that the validities of the GRE for predicting successful completion of graduate training were effectively zero.

This means that no-one knows what "intelligence" is after 100 years of feverish "research". This is especially disconcerting if viewed against the historical background of the mental test movement which Jensen and his followers have tried to revive by linking untenable validity claims for IQ to equally specious "heritability" claims (see Quantitative Behavior Genetics, below)..

Thus, Spearman's Hypothesis does not warrant any of the farreaching claims Jensen and some of his followers (e.g., Herrnstein and Murray) have attached to it. In particular, it does not validate the existence of a general ability g as Jensen has asserted. Nor does it have any bearing on the race question."

Quantitative Behavior Genetics

"One reason for the astonishing persistence of the IQ myth in the facce of overwhelming prior and posterior odds against it may be the unbroken chain of excessive "heritability" claims for "intelligence", which IQ tests are supposed to "measure". However, if "intelligence" is undefined, and Spearman's g is beset with numerous problems, not the least of which is universal (and by now tacitly though grudgingly acknowledged) rejection of Spearman's model by the data, then how can the heritability of "intelligence" exceed that of milk production of cows and egg production of hens?

These problems are addressed in a series of more recent publications, [54, 60, 61, 62, 63, 70, 71, 72, 75, 81]. In [70] it is shown that a once widely used "heritability estimate" is mathematically unsound, because Holzinger had made a mistake in his derivations which had been overlooked for decades. Another such estimate, though mathematically valid, never fits any real data. This should have been obvious from the start because it typically produces an inordinate number of inadmissible estimates (e.g., proportions larger than 1). These absurd results nevertheless found their way into print without comment or challenge. The same estimate also produces excessive "heritabilities" for variables which plainly have nothing to do with genes. For example, the "heritability" of answers to the question: "Did you have your back rubbed last year?" turns out to be 92% for males and 21% for females [81].

The main problem is that all such estimates rely on simplistic mathematical models which necessarily make some unrealistically stringent assumptions. Unfortunately, they were rarely tested. Once they are tested, one finds that they are usually violated by the data. A comprehensive review of these issues is attempted in [81], where further references to specific subproblems can be found. "

Complete information can be found here http://www.psych.purdue.edu/~phs/research.htm

 

[Mandrake]

They didn't just measure head circumference. They measured brain volume as well, and even broke it down further by size of some other brain regions. They used head circumference because it is an easy measure that is related to malnutrition during infancy and early childhood and were looking to see if it was a consistent predictor of brain volume and IQ.

The obvious problem with the use of head circumference as a proxy for brain volume is that it introduces a significant error in estimating brain volume.

Much of this difference is well-established as relating to areas involved in sexual behavior, reproductive function, maternal behavior. Besides, the two facts you present together don't indicate any difference in neuronal number, just that the density of neurons is greater in women than men, so their brains are more compact. This is far too simplistic though, since there are some brain areas that are larger in women than men. It relates to gender-specific brain functions.

Since this subject interests you, I have a few items that pertain to it:
The g Factor: Intelligence, Income, Inequality
by Edward M. Miller
Mankind Quarterly, Vol. 39 (Spring 1999) No. 3, 337-354

It is well established that female brains are smaller than male brains, and also that g correlates with brain size. Thus it is surprising that there is no sex difference in g. Jensen attempts to resolve this by noting that "the sex difference in brain size may be best explained in terms of the greater 'packing density' of neurons in the female brain, a sexual dimorphism that allows the same number of neurons in the male and female brains despite their differences in gross size." (p541). The major problem with this theory is evolutionary, if one can obtain the same performance by packing the neurons closer together, this would presumably save energy and reduce birth difficulties. One naturally asks why such a superior design was adapted for female brains, but not for male brains. Another possibility is that the extra brain matter in males is used for some function males excel at, such as spatial visualization. To me this is far more plausible.
===
Kings of Men: Introduction to a Special Issue of the Journal of INTELLIGENCE (1998)
by DOUGLAS K. DETTERMAN

We now know quite conclusively from MRI studies, for example, that IQ is correlated with brain size, but we still don't know what precisely it is about brain size that causes this correlation.
===
MYOPIA, INTELLIGENCE, AND THE EXPANDING HUMAN NEOCORTEX
[International Journal of Neuroscience (1999), 98(3-4): 153-276]
Precis of Storfer on Brain-Intelligence

Supporting this proposed construct are findings that: (1) in rodents, exposure to an unusual amount of visual complexity (coupled with novelty) induces neuronal enlargement in the expected areas (and layers) of the neocortex, with these postmortem effects heightened with multigenerational exposure; and (2) intellectually gifted people have grossly enlarged neurons in the areas associated with their specific gift or talent (see section 3.3), especially in the cortical layers that interconnect distant association areas (III; V), and the layer between (IV), which connects cortex with thalamus.

It is further proposed that the markedly greater likelihood of females with high IQs having myopia compared with equivalent-IQ males (see section 2.1) reflects the smaller size of the female brain (males have roughly 15% more neocortical neurons, but, interestingly, only a 2% larger thalamus). Since females perform almost as well as males in the two-dimensional spatial-analysis components of IQ tests, it would seem to follow that, to cope with the visual complexity of a modern urban environment, a greater stress would be placed on the female's available neuronal resources. Thus, a proportionately larger visual pathway would be generated in females to accommodate the additional attentional strain.

Based on the article I cited above, this would indicate we should be seriously looking into the extent of malnutrition among the black population in the US, especially in pre-school aged children, since it seems nutritional interventions for school-aged children may be too late to help.

Why so? Your comment implies that malnutrition affects most blacks in the US, but not whites. It doesn't add up, since the W-B IQ gap is largest at the highest SES level and lowest at the lowest SES level. Is malnutrition related to SES? If so, wouldn't it make sense that the higher SES levels would have better nutrition? Likewise, would you support seriously looking at the malnutrition in Hispanics, non-Hispanic whites, and Asians with respect to Ashkenazi Jews? Is it likely that Asians have malnutrition that causes them to have a mean IQ below that of Ashkenazi Jews? If you are unfamiliar with the relative brain size findings this may be helpful:

Is There a Biological Basis for Race and Racial Differences?
By J. Philippe Rushton
Insight, May 28, 2001

What I've found is that in brain size, intelligence, temperament, sexual behavior, fertility, growth rate, life span, crime, and family stability, Orientals fall at one end of the spectrum, blacks fall at the other end and whites fall in between. On average, Orientals are slower to mature, less fertile, and less sexually active, and have larger brains and higher IQ scores. Blacks are at the opposite end in each of these areas. Whites fall in the middle, often close to Orientals.

The relation between brain size and intelligence has been shown by dozens of studies, including state-of-the-art magnetic resonance imaging. Orientals average 1 cubic inch more brain matter than Whites, and Whites average a very large 5 cubic inches more than Blacks. Since one cubic inch of brain matter contains millions of brain cells and hundreds of millions of nerve connections, brain size differences help to explain why the races differ in IQ.

Racial differences in brain size show up early in life as well. The U.S. Collaborative Perinatal Project followed more than 50,000 children from birth to seven years. In the 1997 issue of the journal Intelligence, I showed that these Orientals had larger brains than Whites at birth, four months, one year, and seven years; the Whites had larger brains than Blacks at all ages. In the United States, Orientals are seen as a "model minority." They have fewer divorces, out-of-wedlock births, and fewer reports of child abuse than Whites. More Orientals graduate from college and fewer go to prison. Blacks, on the other hand, are 12% of the American population but make up 50% of the prison population.

Genes play a big part in athletic ability, brain size, IQ, and personality. Trans-racial adoption studies, where infants of one race are adopted and reared by parents of a different race, provide some of the strongest evidence. Oriental children, even if malnourished before being adopted by white parents, go on to have IQs above the white average. Black infants adopted into middle-class white families end up with IQs lower than the white average.

The myelination hypothesis seems to be in contradiction to the summary you posted of work by Haier's group, which stated that it was gray matter volume that is important to IQ. Gray matter is gray because it is unmyelinated. Though, white matter and gray matter are pretty archaic terms.

Ed Miller's hypothesis is based on large numbers of supporting observations, all of which support his neural noise model. He argues that the role of myelination is to reduce the cascading effects of neural noise as the brain sends pulses from one place to another.

What statistic is being used for these correlations? I'm accustomed to correlations being reported as an r-value, where 0 is no correlation and 1 is a high correlation.

A correlation coefficient of 1 is not just high, it is absolute.

Any correlation near 0.5 would be pretty equivocal, and something as close to zero as .1 or .2 would mean there is no correlation at all.

Murray and Herrnstein: "A crucial point to keep in mind about correlation coefficients, now and throughout the rest of the book, is that correlations in the social sciences are seldom much higher than .5 (or lower than -.5) and often much weaker -- because social events are imprecisely measured and are usually affected by variables besides the ones that happened to be included in any particular body of data. A correlation of .2 can nevertheless be "big" for many social science topics. In terms of social phenomena, modest correlations can produce large aggregate effects. Witness the prosperity of casinos despite the statistically modest edge they hold over their customers." [The Bell Curve, page 67]

Another example of small, but meaningful and robust correlations is inbreeding depression. This phenomenon is observed to affect numerous traits, including IQ and is consistently mentioned in psychometric texts as one of the most indisputable proofs of the strong genetic component of intelligence. When inbreeding is very close (siblings or parent-child), the effect is quite large; but most studies are based on first cousins, where effects on physical traits are typically .05 sigma to .10 sigma. [Jensen reports a number of studies pertaining to inbreeding depression in his book The g Factor. See the chapter titled “The Heritability of g.”]

In either case, correlation does not mean causation,

Have there been any suggestions here to the contrary?

 

[Mandrake]

So, regardless of a person's qualifications, you won't believe them unless they are a psychometrician,

True, when they assert positions that are inconsistent with well established findings. The sources you seek are selected on the basis that they must be left-wing liberal propaganda.

ok, here's a Ph.D. in Psychometrics.

Schönemann is a known quantity. I have read some of his material before. You can believe whatever you wish, but I do not accept his or any other person's assertions when they are simply outrageous. Some of the material you quoted from him is just that. Would you care to explain the error that is supposed to have been made by Holzinger? I assume you understand it (I do not) or you would not have cited it. I await the details.

So, if you were going to hire someone to represent you in court, would you select a psychometrician or a lawyer? Do you understand why this question is related to your recent comments?

 

[Nereid]

Psychometrics and intelligence

Is ‘psychometrics’ essentially synonymous with ‘(the study of) intelligence’ (per Mandrake), or is it much broader, with the intelligence part being only a minor component?
http://www.fordham.edu/aps/whatpsy.html , from Fordham University re their PhD program in psychometrics, suggests the latter; e.g. "Of course the most obvious area in which psychometricians are employed is in psychological testing. Testing, whether it be of intelligence, personality, achievement, aptitudes, interests, or proficiency, is a widespread and important practice in our society. […]Psychometricians are not limited to working within the testing industry however. Many psychometricians are employed in industrial and organizational settings performing job analyses, consumer surveys, developing and validating personnel selection procedures, and performing market research. Positions in private and public consulting agencies, clinical research positions, and positions in managerial and administrative roles are also open to graduates of psychometric programs." (my emphasis)

Clarification please!

 

[Nereid]

_g_ and the individual

Suppose I want to know my _g_ and how it may vary. I understand that I can take a test (e.g. an IQ test with high _g_ loading), some chronometric tests, or an EEG. From just one test – of any of these three kinds – what +/- number would my _g_ come with? What is the distribution (e.g. Gaussian)? How does each type of test vary wrt this +/-?

Since _g_ has to do with my brain, and I know all kinds of things affect the performance of ‘brain tasks’, I’m sure psychometricians have done extensive research into the effects of the following on one’s _g_, as estimated by one of the three kinds of _g_ tests:
- alertness, e.g. taking the test mid-morning after a good night’s sleep vs one taken at 2am
- drugs, e.g. caffeine, alcohol, anti-histimines; especially those which are known to affect reaction times and medications for mental conditions
- pain, esp headaches
- general wellness/fitness, e.g. fever, top physical form, hunger,
- brain affecting illnesses or conditions, e.g. epilepsy, depression, Alzheimers, tumour, physical injury, PTSS
- mood
- age

How do estimates of _g_ vary for each of these classes of factors?

(I see that hitssquad has partly answered some of these questions)

 

[Nereid]

'placebo effect' in psychometrics?

Humans are complex animals, and their behaviour a rich field of study. In medicine, a rather paradoxical but well attested effect is the ‘placebo effect’ – giving someone an injection, or a pill results in an objectively observed difference (from not giving one), even if the contents are otherwise known to have no effect. A slightly less paradoxical effect is the ‘white coat effect’ – e.g. some people’s blood pressure is higher in the presence of a white-coated doctor (or blood pressure equipment).

Tests of _g_ also involve human interaction, either tester with subject or machine with subject.

What has psychometric research – not just in intelligence – shown wrt effects somewhat analogous to the placebo or white coat effects? How does the act of administering a psychometric test affect the subject (either consciously, or, more importantly subconsciously)?

 

[Nereid]

the bell curve

I was not in the US when the book was published, but my reading seems to indicate it generated quite a deal of controversy. Mandrake has said that it received few, if any, negative reviews of comments from psychometricians. Indeed, the APA’s review had some favourable things to say about its presentation of the generally accepted scientific results.

However, it would seem that the book contained far more than a dispassionate summary of the then status of a field of science – it also talked about social programs, genetics, politics, and a favourite obsession of 20th century US society, race. If so (I’ve not read the book, so I can’t myself comment on how extensive, or impartial, the authors were on these topics), it would seem entirely appropriate for criticisms of the book to be made from any of these perspectives.

How clearly did the book present the scientific results? E.g. how well did the tentative, provisional nature of all science come across? How was the study of intelligence (a branch of psychology) contextualised wrt neuroscience? Biology? Genetics? Other parts of psychology?

Around the time of the publication of the book, some 50 people signed their names to an ad in a leading US newspaper, on race and intelligence (if memory serves). IIRC, all but four were at US academic institutions. How many were active psychometricians? In the psychometric field of intelligence studies? At the time, how many professional psychometricians were there in US academic institutions?

 

[hitssquad]

Your brain is irreversibly rotting as you read this

Since _g_ has to do with my brain, and I know all kinds of things affect the performance of ‘brain tasks’, I’m sure psychometricians have done extensive research into the effects of the following on one’s _g_, as estimated by one of the three kinds of _g_ tests:
- drugs, e.g. caffeine, alcohol, anti-histimines; especially those which are known to affect reaction times and medications for mental conditions

Reaction time is composed of decision time and motor time. Caffeine may affect motor time, but AFAIK it has not been shown to affect decision time. Other drugs such as Bacopa Monniera (AKA the ayervedic herb Brahmi) may affect decision time, as Bacopa itself has been shown to affect the related variable inspection time and has been shown to increase g (as measured by standard psychometric batteries in a controlled study).

- age

g is known to smoothly drop in adults with age, as I have mentioned many times on Physics Forums and which I mentioned many times as a raison d'être for anti-senescence efforts.

This page has a nice graph of what is likely happening to you as you read this:
http://hiqnews.megafoundation.org/Definition_of_IQ.html

Age-related cognitive decline is also being discussed over at the Children of Millennium forums:

• As you age beyond the age of 18, your physical brain-decay (glycoxidation; amyloid beta build-up; mitochondrial damage; DNA damage) can be clearly watched in slow motion in the form of your raw scores predictably dropping point by point, year by year.
  
  IQ scores on IQ tests correct for this post-18 brain rot, and you are given a same-age-peers curve-graded IQ score (in addition to being allowed to cheat with a massively-larger vocabulary than your g would otherwise imply -- boosted vocabulary subtest scores via vocab cheating by oldsters on the Weschler averages +.80 S.D. {and that's not counting the other free full-scale IQ points they get because their peers have physical brain rot}, according to a brand new study {see at the bottom of this post Verhaeghen; see also MacLullich, et al}).

 

[nuenke]

I came across a recent study that looks at intelligence and specific areas or patches of gray matter. They did not do a correlation as such, but it does look like they are locating those areas related to g, as well as other factors like fatty tissue around axons, glucose uptake, etc. But at least the IQ vs. Brain size is getting narrowed down to IQ and specific brain reqions.

 

[Nereid]

The APA report addresses some issues quite well; it addresses others incompletely; and it misrepresents some issues. Consider the discussion about heritability. They discuss only MZA data and say nothing about path analysis. Why? The results are in agreement, but the literature claims are that path analysis is more robust. In this area, they had no way of knowing what would later be discovered by Dr. Paul Thompson at UCLA: "We were stunned to see that the amount of gray matter in frontal brain regions was strongly inherited, and also predicted an individual's IQ score..." His work was done with MRI. Their coverage of the Scarr-Weinberg findings was poor.

It seems that there may be more than one 'APA report'; could someone please tell me whether http://www.apa.org/releases/intell.html is the one we're discussing?

"APA Task Force Examines the Knowns and Unknowns of Intelligence

1996 Press Release
What is intelligence and can it be measured? These questions have fueled a continuing debate about whether intelligence is inherited, acquired, environmental, or a combination of these and other factors. In a field where so many issues are unresolved and so many questions unanswered, the confident tone that has characterized most of the debate on these topics is clearly out of place, according to a new report by the American Psychological Association (APA).

The report, entitled 'Intelligence: Knowns and Unknowns,' was written by APA's Task Force on Intelligence. The task force convened in January 1995 to prepare a dispassionate and authoritative report in response to the fall 1994 publication of Herrnstein and Murray's The Bell Curve. 'Their book sparked a new and vigorous round of debate about the meaning of intelligence test scores and the nature of intelligence itself, a debate in which little effort was made to distinguish scientific issues from political ones,' stated Ulric Neisser, PhD, chair of the task force.

Because there are many ways to be intelligent, there are also many conceptualizations of intelligence. Standardized intelligence test scores (IQs), which reflect a person's standing in relation to his or her generational peers, are based on tests that measure a number of different abilities. Psychometric testing, the use of standardized tests to assess specific abilities, has generated the most systematic research though many questions remain unanswered. According to the task force report:

* Intelligence test scores partially predict individual differences in school achievement, such as grade point average and number of years of education that individuals complete. In this context, the skills measured are important. Nevertheless, population levels of school achievement are not determined solely or even primarily by intelligence or any other individual-difference variable. The fact that children in Japan and Taiwan learn much more math than their peers in America, for example, can be attributed primarily to differences in culture and schooling rather than in abilities measured by intelligence tests.

* Test scores also correlate to some extent with measures of accomplishment outside of school, for example adult occupational status. This correlation is linked with school achievement because, in the United States today, high test scores and grades are prerequisites for entry into many careers and professions. However, a significant correlation between test scores and occupational status remains even when education and family background have been statistically controlled.

* Differences in genetic endowment contribute substantially to individual differences in (psychometric) intelligence, but the pathway by which genes produce their effects is still unknown. The impact of genetic differences appears to increase with age, but it is not known why.

* Environmental factors contribute substantially to the development of intelligence, but it is not clearly understood what those factors are or how they work. Attendance at school is certainly important, for example, but it is not known what aspects of schooling are critical.

* The role of nutrition in intelligence remains obscure. Severe childhood malnutrition has clear negative effects, but the hypothesis that certain 'micro- nutrients' may affect intelligence in otherwise adequately-fed populations has not been convincingly demonstrated.

* The differential between the mean intelligence test scores of Blacks and Whites does not result from any obvious biases in test construction and administration, nor does it simply reflect differences in socio-economic status. Explanations based on factors of caste and culture may be appropriate, but so far there is little direct empirical support for them. There is certainly no such support for a genetic interpretation. At this time, no one knows what is responsible for the differential.

* It is widely agreed that standardized tests do not sample all forms of intelligence. Obvious examples include creativity, wisdom, practical sense, and social sensitivity, among others. Despite the importance of these abilities, very little is known about them, how they develop, what factors influence their development, and how they are related to more traditional measures.

* Although there are no important sex differences in overall intelligence test scores, substantial differences do appear for specific abilities. Males typically score higher on visual-spatial and (beginning in middle childhood) mathematical skills; females excel on a number of verbal measures. Sex hormone levels are clearly related to some of these differences, but social factors presumably play a role as well.

The task force distinguishes sharply between scientific research and political rhetoric. 'The study of intelligence does not need politicized assertions and recriminations; it needs self-restraint, reflection, and a great deal more research.' According to the report, the questions that remain are socially as well as scientifically important and 'that there is no reason to think them unanswerable, but finding the answers will require a shared an sustained effort as well as the commitment of substantial scientific resources.'

The American Psychological Association (APA), in Washington, DC, is the largest scientific and professional organization representing psychology in the United States and is the world's largest association of psychologists. APA's membership includes more than 132,000 researchers, educators, clinicians, consultants and students. Through its divisions in 49 subfields of psychology and affiliations with 58 state and territorial and Canadian provincial associations, APA works to advance psychology as a science, as a profession and as a means of promoting human welfare.

 

[Nereid]

• High g Loading
  Matrix relations (.94)
  Generalizations (.89)
  Series completion (.87)
  Verbal analogies (.83)
  Likeness relations (.77)
  Problem arithmetic (.77)
  Paragraph comprehension (.73)
  Perceptual analogies (.70)
  
  [...]
  
  • The knowledge and skills tapped by mental test performance merely provide a vehicle for the measurement of g. Therefore, we cannot begin to fathom the causal underpinning of g merely by examining the most highly g-loaded psychometric tests.
  (Ibid. p74.)

• If 'matrix relations' tests have a _g_ loading of 0.94, what else is there is in these tests? In well constructed matrix relations tests, what is the typical individual variance (i.e. an individual takes the same (type of) test many times)?

 

[Nereid]

Contrarily, research has demonstrated that:

• There are plausible reasons ... for assuming that individual differences in g have an approximately normal, or Gaussian ("bellshaped"), distribution, at least within the range of ±2σ from the mean. That range is equivalent to IQs from 70 to 130 on the typical IQ scale (i.e., μ = 100, σ = 15).

(Arthur Jensen. The g Factor. p88.)

Does Jensen go on to say what those 'plausible reasons' are? Subsequent to when Jensen wrote this, what research has been done to establish what that distribution actually is? Why did Jensen add the caveat "within the range of ±2σ from the mean"?

 

[Nereid]

Based on the article I cited above, this would indicate we should be seriously looking into the extent of malnutrition among the black population in the US, especially in pre-school aged children, since it seems nutritional interventions for school-aged children may be too late to help.

Why so? Your comment implies that malnutrition affects most blacks in the US, but not whites. It doesn't add up, since the W-B IQ gap is largest at the highest SES level and lowest at the lowest SES level. Is malnutrition related to SES? If so, wouldn't it make sense that the higher SES levels would have better nutrition? Likewise, would you support seriously looking at the malnutrition in Hispanics, non-Hispanic whites, and Asians with respect to Ashkenazi Jews? Is it likely that Asians have malnutrition that causes them to have a mean IQ below that of Ashkenazi Jews?

Where to begin to untangle this?

For a start, sentences in English with comparatives ('most', 'higher') don't help IMHO; the reality of population groups is very rich, and teasing apart the influences of multiple factors calls for hard thought.

Take the Black and White SES: if early childhood malnutrition contributes, then you would need to know about the relative experiences of groups who are now in their 40s to 60s. Cet par it may very well be that 'the higher SES levels would have better nutrition', but my impression is that in 21st century US society things are most certainly not otherwise equal.

Take Asians: my impression is that a significant proportion of Asians in the US are migrants or children of migrants; further, with some notable exceptions, they are primarily 'economic migrants' - they made conscious choices and effort to migrate. In this sense, the 'control group' of whites would be those who arrived in the US several centuries ago (and there'd be no black control group; unless I have misread my US history, most folk who came from Africa didn't make get a choice).

is anything If you are unfamiliar with the relative brain size findings this may be helpful:

Is There a Biological Basis for Race and Racial Differences?
By J. Philippe Rushton
Insight, May 28, 2001

What I've found is that in brain size, intelligence, temperament, sexual behavior, fertility, growth rate, life span, crime, and family stability, Orientals fall at one end of the spectrum, blacks fall at the other end and whites fall in between. On average, Orientals are slower to mature, less fertile, and less sexually active, and have larger brains and higher IQ scores. Blacks are at the opposite end in each of these areas. Whites fall in the middle, often close to Orientals.

The relation between brain size and intelligence has been shown by dozens of studies, including state-of-the-art magnetic resonance imaging. Orientals average 1 cubic inch more brain matter than Whites, and Whites average a very large 5 cubic inches more than Blacks. Since one cubic inch of brain matter contains millions of brain cells and hundreds of millions of nerve connections, brain size differences help to explain why the races differ in IQ.

Racial differences in brain size show up early in life as well. The U.S. Collaborative Perinatal Project followed more than 50,000 children from birth to seven years. In the 1997 issue of the journal Intelligence, I showed that these Orientals had larger brains than Whites at birth, four months, one year, and seven years; the Whites had larger brains than Blacks at all ages. In the United States, Orientals are seen as a "model minority." They have fewer divorces, out-of-wedlock births, and fewer reports of child abuse than Whites. More Orientals graduate from college and fewer go to prison. Blacks, on the other hand, are 12% of the American population but make up 50% of the prison population.

Genes play a big part in athletic ability, brain size, IQ, and personality. Trans-racial adoption studies, where infants of one race are adopted and reared by parents of a different race, provide some of the strongest evidence. Oriental children, even if malnourished before being adopted by white parents, go on to have IQs above the white average. Black infants adopted into middle-class white families end up with IQs lower than the white average.

I trust this is a piece of journalism and not a scientific paper; I sincerely hope that Rushton has done good science to back each of the points he makes here. In particular, I would expect that he has done studies in other countries, to demonstrate (for example) that he's not just reporting on some unique, US, human condition.

 

[Mandrake]

Suppose I want to know my _g_ and how it may vary. I understand that I can take a test (e.g. an IQ test with high _g_ loading), some chronometric tests, or an EEG. From just one test – of any of these three kinds – what +/- number would my _g_ come with? What is the distribution (e.g. Gaussian)? How does each type of test vary wrt this +/-?

Since most observers do not have the laboratory devices and skills to measure intelligence via chronometric or electroencephalography techniques, the most common approach is to use an IQ test. As you probably know there are very many IQ tests, although only a few of them are used in most serious research. Of these the Raven's is most often cited in research programs. The WAIS versions are also widely used. For most tests, _g_ has to be extracted by weighting the subtest scores according to their _g_ loadings. Obviously, different tests will have different _g_ loadings, different subtest structures, and different associated errors. As with measuring physical phenomena (consider temperature) there are errors that can be identified in connection with many aspects of the measurement. Most of these errors are small. Ultimately the reliability coefficient is of central importance. Jensen: "The difference between the reliability coefficient and unity represents the proportion of the total variance of the measurements that is attributed to measurement error. ... In my laboratory we have been able to measure such variables as memory span, flicker-fusion frequency (a sensory threshold), and reaction time with reliability coefficients greater than .99. ... The reliability coefficients for multi-item tests of more complex mental processes, such as measured by typical IQ tests, are generally about .90 to .95. This is higher than the reliability of people's height and weight measured in a doctor's office! The reliability coefficients of blood pressure measurements, blood cholesterol level, and diagnosis based on chest X-rays are typically around .50." [The _g_ Factor, P. 50]

The concept of TRUE SCORE is related.
Regressed true score = [(reliability coefficient) x (test score - mean score for population)] + (mean score for population)
This is obviously a hypothetical score that attempts to factor out measurement error. For a very detailed discussion of all things related to measurement error, see Jensen, A.R. (1980). Bias in mental testing. New York: Free Press. Jensen says that tests with reliability coefficients of less than .90 should (generally) not be used.

Since _g_ has to do with my brain, and I know all kinds of things affect the performance of ‘brain tasks’, I’m sure psychometricians have done extensive research into the effects of the following on one’s _g_, as estimated by one of the three kinds of _g_ tests:
- alertness, e.g. taking the test mid-morning after a good night’s sleep vs one taken at 2am
- drugs, e.g. caffeine, alcohol, anti-histimines; especially those which are known to affect reaction times and medications for mental conditions
- pain, esp headaches
- general wellness/fitness, e.g. fever, top physical form, hunger,
- brain affecting illnesses or conditions, e.g. epilepsy, depression, Alzheimers, tumour, physical injury, PTSS
- mood
- age

How do estimates of _g_ vary for each of these classes of factors?

I don't have a source at hand with a ready answer. When an IQ test is given, it is the responsibility of the test administrator to determine that the person taking the test is fully alert and not encumbered by factors that would render the test inaccurate. Some tests, such as the WAIS are age adjusted.

 

[Mandrake]

Nereid:

What has psychometric research – not just in intelligence – shown wrt effects somewhat analogous to the placebo or white coat effects? How does the act of administering a psychometric test affect the subject (either consciously, or, more importantly subconsciously)?

There are various papers that have examined the conditions of test taking. The range of things considered includes, for example, stress. Jensen used pulse rate to measure stress, but found that it did not significantly affect scores. A placebo effect would imply that something causes the person taking the test to score artifically high. I am unaware of any such finding. There are also various reports that such things as stimulants or even music can temporarily boost test scores. Presumably these findings indicate an induced error in the positive direction, since no findings have reported permanent improvements in intelligence due to such factors.

 

[Mandrake]

I was not in the US when the book was published, but my reading seems to indicate it generated quite a deal of controversy.

There were a lot of people who were unaware of the findings reported in The Bell Curve. When I saw it, I was amazed to see that virtually every item in it had been previously reported in even greater detail. It was basically old science, but suddenly hit uninformed people in the face. Instead of trying to understand it, they reacted by writing ignorant missives in newspapers and magazines.

The Bell Curve can be divided into three parts:
1 - a detailed summary of history, research findings, and theories (including some of the unsound ones)
2 - an analysis of the National Longitudinal Study of Youth
3 - a discussion of the social and economic impacts that may relate to 1 and

If so (I’ve not read the book, so I can’t myself comment on how extensive, or impartial, the authors were on these topics), it would seem entirely appropriate for criticisms of the book to be made from any of these perspectives.

It is fair to argue item 3 forever. People have different views. Items 1 and 2 are matters of science and, if they are to be disputed, must be disputed on scientific grounds, not emotional ones. The basic rant that came from journalists was something to the effect that god made all men equal and, therefore, they must all be equally intelligent. Some people even cited the Declaration of Independence to demonstrate that blacks do not have a mean IQ of 85.

How clearly did the book present the scientific results?

Very clearly and very carefully. Most of items 1 and 2 were understated and supported by massive parallel findings. That is to say that to make a simple point, the authors cited findings from many independent studies, different countries, and different time frames, all reaching the same conclusion. In instances where there were conflicting findings, they clearly stated so. The book was written in a form that made it easy to read, by comparison to the typical Jensen textbooks.

E.g. how well did the tentative, provisional nature of all science come across?

The book was not intended to address all science and it did not. It was also not a general discussion of philosophy.

How was the study of intelligence (a branch of psychology) contextualised wrt neuroscience? Biology? Genetics? Other parts of psychology?

These issues were discussed to the degree that was possible one decade ago. There have been important findings since that time, especially in connection with laboratory measurements. Jensen, A. R. (1998). The g factor: The science of mental ability. Westport, CT: Praeger is a much better present day reference book.

Around the time of the publication of the book, some 50 people signed their names to an ad in a leading US newspaper, on race and intelligence (if memory serves).

The newspaper was the Wall Street Journal, Tuesday, December 13, 1994. The letter it printed was written by Linda Gottfredson, although it was not attributed to her. It was signed by, as I recall, 52 scholars.

IIRC, all but four were at US academic institutions.

Close. I just counted six. Detterman reported (in Intelligence) the details of how, why, and under what conditions that letter was written. There are very good reasons behind its final form and the people who signed it.

How many were active psychometricians? In the psychometric field of intelligence studies? At the time, how many professional psychometricians were there in US academic institutions?

To the best of my knowledge all of them, but I haven't looked up the lesser known people.

 

[Mandrake]

Does Jensen go on to say what those 'plausible reasons' are? Subsequent to when Jensen wrote this, what research has been done to establish what that distribution actually is? Why did Jensen add the caveat "within the range of ±2σ from the mean"?

This subject is discussed in much more detail in Bias in Mental Testing, Chapter 4. For example, Jensen wrote: "The simple fact is that a test unavoidably yields a near normal distribution when it is made up of (1) a large number of items, (2) a wide range of item difficulties, (3) no marked gaps in item difficulties, (4) a variety of content or forms, and (5) items that have a significant correlation with the sum of all other item scores, so as to ensure that each item in the test measures whatever the test as a whole measures." He goes on to point out that it would take a lot of effort to produce a test that is so screwed up that it would not produce a distribution that "departs at all radically from the normal."

 

[hitssquad]

Linda Gottfredson is a 'psychometrician'?

The newspaper was the Wall Street Journal, Tuesday, December 13, 1994. The letter it printed was written by Linda Gottfredson,

How many were active psychometricians? In the psychometric field of intelligence studies? At the time, how many professional psychometricians were there in US academic institutions?

To the best of my knowledge all of them, but I haven't looked up the lesser known people.

Gottfredson is a sociologist.