Tuesday, March 20, 2007

Intelligence quotient

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IQ tests are designed to give approximately this Gaussian distribution. Colors delineate one standard deviation.
IQ tests are designed to give approximately this Gaussian distribution. Colors delineate one standard deviation.

An intelligence quotient or IQ is a score derived from one of several different standardized tests attempting to measure intelligence. IQ tests are generally designed and used because they are found to be predictive of later intellectual achievement, such as educational achievement. IQ also correlates with job performance and income, although in all cases other factors explain most of the variance. Recent work has demonstrated links between IQ and health.

The average IQ scores for many populations were rising rapidly during the 20th century: a phenomenon called the Flynn effect. It is not known whether these changes in scores reflect real changes in intellectual abilities (if not, then this raises questions about what IQ tests do measure).



[edit] History

In 1905 the French psychologist Alfred Binet published the first modern intelligence test, the Binet-Simon intelligence scale. His principal goal was to identify students who needed special help in coping with the school curriculum. Along with his collaborator Theodore Simon, Binet published revisions of his intelligence scale in 1908 and 1911, the last appearing just before his untimely death.

In 1912, the abbreviation of "intelligence quotient" or I.Q., a translation of the German Intelligenz-Quotient, was coined by the German psychologist William Stern. A further refinement of the Binet-Simon scale was published in 1916 by Lewis M. Terman, from Stanford University, who incorporated Stern's proposal that an individual's intelligence level be measured as an intelligence quotient (I.Q.). Terman's test, which he named the Stanford-Binet Intelligence Scale formed the basis for one of the modern intelligence tests still commonly used today.

Originally, IQ was calculated with the formula 100 \times \frac{\text{mental age}}{\text{chronological age}}.

A 10-year-old who scored as high as the average 13-year-old, for example, would have an IQ of 130 (100*13/10).

In 1939 David Wechsler published the first intelligence test explicitly designed for an adult population, the Wechsler Adult Intelligence Scale, or WAIS. Since publication of the WAIS, Wechsler extended his scale downward to create the Wechsler Intelligence Scale for Children, or WISC, which is still in common usage. The Wechsler scales contained separate subscores for verbal and performance IQ, thus being less dependent on overall verbal ability than early versions of the Stanford-Binet scale, and was the first intelligence scale to base scores on a standardized normal distribution rather than an age-based quotient.

Because age-based quotients only worked for children, it was replaced by a projection of the measured rank on the Gaussian bell curve with a center value (average IQ) of 100, and a standard deviation of 15 or occasionally 16. Thus the modern version of the IQ is a mathematical transformation of a raw score (based on the rank of that score in a normalization sample; see quantile, percentile, percentile rank), which is the primary result of an IQ test. To differentiate the two scores, modern scores are sometimes referred to as "deviance IQ", while the age-specific scores are referred to as "ratio IQ". While the two methodologies yield similar results near the middle of the bell curve, the older ratio IQ's yielded far higher scores for the intellectually gifted-Marilyn vos Savant appeared in the Guinness book of world records for obtaining a ratio IQ of 228. Such stratospheric numbers are not possible on the deviation IQ because a perfectly Gaussian curve defines the highest possible IQ within the United States (population 300 million) as between five and six standard deviations above the U.S. mean defined as 100. With a standard deviation of 15 this would produce a result of IQ175 to IQ180. In addition, IQ tests like the Wechsler were not intended to reliably discriminate much beyond IQ 130, and simply do not contain enough exceptionally difficult items for one to score in the "stratosphere".

Since the publication of the WAIS, almost all intelligence scales have adopted the normal distribution method of scoring. The use of the normal distribution scoring method makes the term "intelligence quotient" an inaccurate description of the intelligence measurement, but I.Q. still enjoys colloquial usage, and is used to describe all of the intelligence scales currently in use.

[edit] How an IQ test works

IQ tests come in many forms, and some tests use a single type of item or question, while other use several different subtests. Most tests yield both an overall score and individual subtest scores.

A typical IQ test requires the test subject to solve a fair number of problems in a set time under supervision. Most IQ tests include items from various domains, such as short-term memory, verbal knowledge, spatial visualization, and perceptual speed. Some tests have a total time limit, others have a time limit for each group of problems, and there are a few untimed, unsupervised tests, typically geared to measuring high intelligence.

To set the scale for an IQ test, a representative sample of the population for which the IQ is made is gathered. IQ tests are calibrated in such a way as to yield a normal distribution, or "bell curve."

Each IQ test, however, is designed and valid only for a certain IQ range. Because so few people score in the extreme ranges, IQ tests usually cannot accurately measure very low and very high IQs.

Various IQ tests measure a standard deviation with different number of points. Thus, when an IQ score is stated, the standard deviation used should also be stated. A result of 124 in a test with a 24-point standard deviation corresponds to a score of 115 in a test with a 15-point deviation.[1]

Where an individual has scores that do not correlate with each other, there is a good reason to look for a learning disability or other cause for the lack of correlation. Tests have been chosen for inclusion because they display the ability to use this method to predict later difficulties in learning.

On average, IQ scores are stable over a person's lifetime. The mean for ages 17 and 18 was correlated r=.86 with the mean for ages 5, 6 and 7, r=.96 with the mean for ages 11, 12 and 13. Nevertheless, IQ scores do change over time. In the same study the average change between age 12 and age 17 was 7.1 IQ points; some individuals changed as much as 18 points.[2]

[edit] High IQ societies

Main article: High IQ society

A high IQ society is an organisation that limits membership to people who are within a certain high percentile of IQ test results. The most well-known is Mensa.

[edit] IQ and general intelligence factor

Modern IQ tests produce scores for different areas (e.g., language fluency, three-dimensional thinking), with the summary score calculated from subtest scores. The average score, according to the bell curve, is 100. Individual subtest scores tend to correlate with one another, even when seemingly disparate in content.

Mathematical analysis of individuals' scores on the subtests of a single IQ test or the scores from a variety of different IQ tests (e.g., Stanford-Binet, WISC-R, Raven's Progressive Matrices, Cattell Culture Fair III, Universal Nonverbal Intelligence Test, and others) find that they can be described mathematically as measuring a single common factor and various factors that are specific to each test. This kind of factor analysis has led to the theory that underlying these disparate cognitive tasks is a single factor, termed the general intelligence factor (or g), that corresponds with the common-sense concept of intelligence.[3] In the normal population, g and IQ are roughly 90% correlated and are often used interchangeably.

Tests differ in their g-loading, which is the degree to which the test score reflects g rather than a specific skill or "group factor" such as verbal ability, spatial visualization, or mathematical reasoning). g-loading and validity have been observed to be related in the sense that most IQ tests derive their validity mostly or entirely from the degree to which they measure g(Jensen 1998).

[edit] Heritability

Main article: Heritability
See also: Inheritance of intelligence

The role of genes and environment (nature and nurture) in determining IQ is reviewed in Plomin et al. (2001, 2003). The degree to which genetic variation contributes to observed variation in a trait is measured by a statistic called heritability. Heritability scores range from 0 to 1, and can be interpreted as the percentage of variation (e.g. in IQ) that is due to variation in genes. Twins studies and adoption studies are commonly used to determine the heritability of a trait. Until recently heritability was mostly studied in children. Some studies find the heritability of IQ around 0.5 but the studies show ranges from 0.4 to 0.8;[4] that is, depending on the study, a little less than half to substantially more than half of the variation in IQ among the children studied was due to variation in their genes. The remainder was thus due to environmental variation and measurement error. A heritability in the range of 0.4 to 0.8 implies that IQ is "substantially" heritable.

It is reasonable to expect that genetic influences on traits like IQ should become less important as one gains experiences with age. Surprisingly, the opposite occurs. Heritability measures in infancy are as low as 20%, around 40% in middle childhood, and as high as 80% in adulthood.[5]

The American Psychological Association's 1995 task force on "Intelligence: Knowns and Unknowns" concluded that within the white population the heritability of IQ is "around .75". It also stated that these particular estimates derive from samples in which the lowest socioeconomic levels were underrepresented (i.e., there were few very poor families), so the range of between family differences was smaller than in the population as a whole. There should be caution in generalizing the findings for between-family effects across the entire social spectrum.[6] The Minnesota Study of Twins Reared Apart, a multiyear study of 100 sets of reared-apart twins which was started in 1979, concluded that about 70% of the variance in IQ was found to be associated with genetic variation.[7] The effect of restriction of range on IQ was examined by Matt McGue and colleagues, who write that "restriction in range in parent disinhibitory psychopathology and family SES had no effect on adoptive-sibling correlations ... IQ".[8]

There are a number of points to consider when interpreting heritability:

  • A high heritability does not mean that the environment has no impact on the development of a trait, or that learning is not involved. Vocabulary size, for example, is very substantially heritable (and highly correlated with general intelligence) although every word in an individual's vocabulary is learned. In a society in which plenty of words are available in everyone's environment, especially for individuals who are motivated to seek them out, the number of words that individuals actually learn depends to a considerable extent on their genetic predispositions.[9]
  • A common error is to assume that because something is heritable it is necessarily unchangeable. This is wrong. Heritability does not imply immutability. As previously noted, heritable traits can depend on learning, and they may be subject to other environmental effects as well. The value of heritability can change if the distribution of environments (or genes) in the population is substantially altered. For example, an impoverished or suppressive environment could fail to support the development of a trait, and hence restrict individual variation. This could affect estimates of heritability.[10] Another example is Phenylketonuria which previously caused mental retardation for everyone who had this genetic disorder. Today, this can be prevented if following a modified diet.
  • On the other hand, there can be effective environmental changes that do not change heritability at all. If the environment relevant to a given trait improves in a way that affects all members of the population equally, the mean value of the trait will rise without any change in its heritability (because the differences among individuals in the population will stay the same). This has evidently happened for height: the heritability of stature is high, but average heights continue to increase.[11]
  • Even in developed nations, high heritability of a trait within a given group has no necessary implications for the source of a difference between groups.[12][13]

[edit] Environment

See also: Health and intelligence

Environmental factors play a role in determining IQ. Proper childhood nutrition appears critical for cognitive development; malnutrition can lower IQ. Other research indicates environmental factors such as prenatal exposure to toxins, duration of breastfeeding, and micronutrient deficiency can affect IQ.

It is well known that it is possible to increase one's IQ score by training, for example by regularly playing puzzle games. Recent studies have shown that training in using one's working memory may increase IQ. (Klingberg et al., 2002)

[edit] Family environment

In the developed world, nearly all personality traits show that, contrary to expectations, environmental effects actually cause non-related children raised in the same family ("adoptive siblings") to be as different as children raised in different families (Harris, 1998; Plomin & Daniels, 1987). There are some family effects on the IQ of children, accounting for up to a quarter of the variance. However, by adulthood, this correlation disappears, such that adoptive siblings are not more similar in IQ than strangers.[14] For IQ, adoption studies show that, after adolescence, adoptive siblings are no more similar in IQ than strangers (IQ correlation near zero), while full siblings show an IQ correlation of 0.6. Twin studies reinforce this pattern: monozygotic (identical) twins raised separately are highly similar in IQ (0.86), more so than dizygotic (fraternal) twins raised together (0.6) and much more than adoptive siblings (~0.0).[15]

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that there is no doubt that normal child development requires a certain minimum level of responsible care. Severely deprived, neglectful, or abusive environments must have negative effects on a great many aspects of development, including intellectual aspects. Beyond that minimum, however, the role of family experience is in serious dispute. Do differences between children's family environments (within the normal range) produce differences in their intelligence test performance? The problem here is to disentangle causation from correlation. There is no doubt that such variables as resources of the home and parents' use of language are correlated with children's IQ scores, but such correlations may be mediated by genetic as well as (or instead of) environmental factors. But how much of that variance in IQ results from differences between families, as contrasted with the varying experiences of different children in the same family? Recent twin and adoption studies suggest that while the effect of the family environment is substantial in early childhood, it becomes quite small by late adolescence. These findings suggest that differences in the life styles of families whatever their importance may be for many aspects of children's lives make little long-term difference for the skills measured by intelligence tests. It also stated "We should note, however, that low-income and non-white families are poorly represented in existing adoption studies as well as in most twin samples. Thus it is not yet clear whether these studies apply to the population as a whole. It re-mains possible that, across the full range of income and ethnicity, between-family differences have more lasting consequences for psychometric intelligence."[16]

A study of French children adopted between the ages of 4 and 6 shows the continuing interplay of nature and nurture. The children came from poor backgrounds with IQs that initially averaged 77, putting them near retardation. Nine years later after adoption, they retook the I.Q. tests, and all of them did better. The amount they improved was directly related to the adopting family’s status. "Children adopted by farmers and laborers had average I.Q. scores of 85.5; those placed with middle-class families had average scores of 92. The average I.Q. scores of youngsters placed in well-to-do homes climbed more than 20 points, to 98."[17]

[edit] Biased older studies?

Stoolmiller (1999) found that the range restriction of family environments that goes with adoption, that adopting families tend to be more similar on for example SES than the general population, means that role of the shared family environment have been understimated in prevous studies. Corrections for range correction applied to adoption studies indicate that SE could account for as much as 50% of the variance in IQ.[18] However, the effect of restriction of range on IQ for adoption studies was examined by Matt McGue and colleagues, who write that "restriction in range in parent disinhibitory psychopathology and family SES had no effect on adoptive-sibling correlations [in] IQ".[19]

Eric Turkheimer and colleagues (2003), not using an adoption study, included impoverished US families. Results demonstrated that the proportions of IQ variance attributable to genes and environment vary nonlinearly with SES. The models suggest that in impoverished families, 60% of the variance in IQ is accounted for by the shared family environment, and the contribution of genes is close to zero; in affluent families, the result is almost exactly the reverse.[20] They suggest that the role of shared environmental factors may have been underestimated in older studies which often only studied affluent middle class families.[21]

[edit] Maternal (foetal) environment

A meta-analysis, by Devlin and colleagues in Nature (1997), of 212 previous studies evaluated an alternative model for environmental influence and found that it fits the data better than the 'family-environments' model commonly used. The shared maternal (foetal) environment effects, often assumed to be negligible, account for 20% of covariance between twins and 5% between siblings, and the effects of genes are correspondingly reduced, with two measures of heritability being less than 50%. They argue that the shared maternal environment may explain the striking correlation between the IQs of twins, especially those of adult twins that were reared apart.[22]

Bouchard and McGue reviewed the literature in 2003, arguing that Devlin's conclusions about the magnitude of hertiability is not substantially different than previous reports and that their conclusions regarding prenatal effects stands in contradiction to many previous reports.[23] They write that:

Chipuer et al. and Loehlin conclude that the postnatal rather than the prenatal environment is most important. The Devlin et al. (1997a) conclusion that the prenatal environment contributes to twin IQ similarity is especially remarkable given the existence of an extensive empirical literature on prenatal effects. Price (1950), in a comprehensive review published over 50 years ago, argued that almost all MZ twin prenatal effects produced differences rather than similarities. As of 1950 the literature on the topic was so large that the entire bibliography was not published. It was finally published in 1978 with an additional 260 references. At that time Price reiterated his earlier conclusion (Price, 1978). Research subsequent to the 1978 review largely reinforces Price’s hypothesis (Bryan, 1993; Macdonald et al., 1993; Hall and Lopez-Rangel, 1996; see also Martin et al., 1997, box 2; Machin, 1996).[24]

[edit] The Dickens and Flynn model

Dickens and Flynn (2001) argue that the arguments regarding the disapperance of the shared family environment should apply equally well to groups separated in time. This is contradicted by the Flynn effect. Changes here have happened too quickly to be explained by genetics. This paradox can be explained by observing that the measure "heritability" includes both a direct effect of the genotype on IQ and also indirect effects where the genotype changes the environment, in turn effecting IQ. That is, those with a higher IQ tend to seek out stimulating environments that further increase IQ. The direct effect can initially have been very small but feedback loops can create large differences in IQ. In their model an environmental stimulus can have a very large effect on IQ, even in adults, but this effect also decays over time unless the stimulus continues (the model could be adapted to include possible factors, like nutrition in early childhood, that may cause permanent effects). The Flynn effect can be explained by a generally more stimulating environment for all people. The authors suggest that programs aiming to increase IQ would be most likely to produce long-term IQ gains if they taught children how to replicate outside the program the kinds of cognitively demanding experiences that produce IQ gains while they are in the program and motivate them to persist in that replication long after they have left the program.[25][26]

[edit] Regression towards the mean

The heritability of IQ measures the extent to which the IQ of children appears to be influenced by the IQ of parents. Because the heritability of IQ is less than 100%, the IQ of children tends to "regress" towards the mean IQ of the population. That is, high IQ parents tend to have children who are less bright than their parents, whereas low IQ parents tend to have children who are brighter than their parents. The effect can be quantified by the equation \hat y = \bar x + h^2 \left ( \frac{m + f}{2} - \bar x \right) where

  • \hat{y} is the predicted average IQ of the children;
  • \bar{x} is the mean IQ of the population to which the parents belong;
  • h2 is the heritability of IQ;
  • m and f are the IQs of the mother and father, respectively.[27]

Thus, if the heritability of IQ is 50%, a couple averaging an IQ of 120 may have children that average around an IQ of 110, assuming that both parents come from a population with a median IQ of 100. If parents average an IQ of 80 they may have children that average around an IQ of 90.

[edit] Mental handicaps

About 75–80 percent of mental handicaps are familial (runs in the family), and 20–25 percent is due to not inherited biological problems, such as chromosomal abnormalities or brain damage.[28] Mild to severe mental disability is a symptom of several hundred single-gene disorders and many chromosomal abnormalities, including small deletions. Based on twin studies, moderate to severe mental disability does not appear to be familial, but mild mental disability does. That is, the relatives of the moderate to severely mentally handicapped have normal ranges of IQs, whereas the families of the mildly mentally handicapped have lower IQs.

IQ score ranges (from DSM-IV):

  • mild mental disability: IQ 50–55 to 70; children require mild support; formally called "Educable Mentally Retarded".
  • moderate disability: IQ 35–40 to 50–55; children require moderate supervision and assistance; formally called "Trainable Mentally Retarded".
  • severe mental disability: IQ 20–25 to 35–40; can be taught basic life skills and simple tasks with supervision.
  • profound mental disability: IQ below 20–25; usually caused by a neurological condition; require constant care.

The rate of mental retardation is higher among females than males, according to a 1991 U.S. Centers for Disease Control and Prevention (CDC) study.[29] This is aggravated by the fact that males, unlike females, do not have a spare X chromosome to offset chromosomal defects.

[edit] IQ and the brain

Modern studies using MRI imaging have found several relations between IQ and neuroanatomy. For example, brain size correlates with IQ (r ≈ 0.4) among adults of the same sex (McDaniel, 2005).

[edit] The Flynn effect

Main article: Flynn effect

The Flynn effect is named after James R. Flynn, a New Zealand based political scientist. He discovered that IQ scores worldwide appear to be slowly rising at a rate of around three IQ points per decade (Flynn, 1999). Attempted explanations have included improved nutrition, a trend towards smaller families, better education, greater environmental complexity, and heterosis (Mingroni, 2004). Tests are therefore renormalized occasionally to obtain mean scores of 100, for example WISC-R (1974), WISC-III (1991) and WISC-IV (2003). Hence it is difficult to compare IQ scores measured years apart, unless this is compensated for. There is recent evidence that the tendency for intelligence scores to rise has ended in some first world countries.

[edit] Group differences

Among the most controversial issues related to the study of intelligence is the observation that intelligence measures such as IQ scores vary between populations. While there is little scholarly debate about the existence of some of these differences, the reasons remain highly controversial both within academia and in the public sphere.

[edit] Health and intelligence

Several factors can lead to significant cognitive impairment, particularly if they occur during pregnancy and childhood when the brain is growing and the blood-brain barrier is less effective. Such impairment may sometimes be permanent, sometimes be partially or wholly compensated for by later growth. Several harmful factors may also combine, possibly causing greater impairment.

Developed nations have implemented several health policies regarding nutrients and toxins known to influence cognitive function. These include laws requiring micronutrient fortification of certain food products and laws establishing safe levels of pollutants (e.g. lead, mercury, and organochlorides). Comprehensive policy recommendations targeting reduction of cognitive impairment in children have been proposed.[30]

[edit] Gender and intelligence

Most studies show that despite sometimes significant differences in subtest scores, men and women have the same average IQ. Women perform better on tests of memory and verbal proficiency for example, while men perform better on tests of mathematical and spatial ability. Although gender-related differences in average IQ are insignificant, male scores display a higher variance: there are more men than women with both very high and very low IQs. The average IQ being 100 could see man have a s.d. of 16 and women a s.d. of 15. Differences in variance would mean that more men are less intelligent than women also.

[edit] Religiosity and intelligence

The topic of Religiosity and Intelligence pertains to possible relationships between intelligence and religious belief.

Topics dealing with the measurement of intelligence are often controversial. Critics in these areas examine the validity and fairness of cognitive testing, as well as the problems in the definition and operationalization of the other measurements under discussion, in this case religiosity. Many of the issues pertaining to the investigation of group differences in intelligence in relation to religiosity are also raised in the investigation of race and intelligence—a better established, though even more controversial, area of intelligence research.

In scientific research, correlations can suggest, but not necessarily imply causation: even if a positive or negative correlation can be found between intelligence and religiosity, it may suggest, but doesn't involve as a necessary circumstance, that one is causing the other. (See also: spurious relationship; and correlation does not imply causation).

[edit] Race and IQ

Main article: Race and intelligence

Much research has been devoted to the extent and potential causes of racial group differences in IQ.

[edit] Positive correlations with IQ

An example demonstrating linear correlations between 1000 pairs of numbers. The data are graphed on the lower left and their correlation coefficients listed on the upper right. Each set of points correlates maximally with itself, as shown on the diagonal (all correlations = +1).
An example demonstrating linear correlations between 1000 pairs of numbers. The data are graphed on the lower left and their correlation coefficients listed on the upper right. Each set of points correlates maximally with itself, as shown on the diagonal (all correlations = +1).
Economic and social correlates of IQ in the USA
IQ <75 75–90 90–110 110–125 >125
U.S. population distribution 5 20 50 20 5
Married by age 30 72 81 81 72 67
Out of labor force more than 1 month out of year (men) 22 19 15 14 10
Unemployed more than 1 month out of year (men) 12 10 7 7 2
Divorced in 5 years 21 22 23 15 9
% of children w/ IQ in bottom decile (mothers) 39 17 6 7 <>
Had a baby outside of marriage (mothers) 32 17 8 4 2
Lives in poverty 30 16 6 3 2
Ever incarcerated (men) 7 7 3 1 <>
Chronic welfare recipient (mothers) 31 17 8 2 <>
High school dropout 55 35 6 0.4 <>
Values are the percentage of each IQ sub-population, among non-Hispanic whites only, fitting each descriptor. Compiled by Gottfredson (1997) from a U.S. study by Herrnstein & Murray (1994) pp. 171, 158, 163, 174, 230, 180, 132, 194, 247–248, 194, 146 respectively.

While IQ is sometimes treated as an end unto itself, scholarly work on IQ focuses to a large extent on IQ's validity, that is, the degree to which IQ predicts or correlations with outcomes such as job performance, social pathologies, or academic achievement. Different IQ tests differ in their validity for various outcomes.

Validity is the correlation between score (in this case cognitive ability, as measured, typically, by a paper-and-pencil test) and outcome (in this case job performance, as measured by a range of factors including supervisor ratings, promotions, training success, and tenure), and ranges between −1.0 (the score is perfectly wrong in predicting outcome) and 1.0 (the score perfectly predicts the outcome). See validity (psychometric).

Research shows that general intelligence plays an important role in many valued life outcomes. In addition to academic success, IQ correlates to some degree with job performance (see below), socioeconomic advancement (e.g., level of education, occupation, and income), and "social pathology" (e.g., adult criminality, poverty, unemployment, dependence on welfare, children outside of marriage). Recent work has demonstrated links between general intelligence and health, longevity, and functional literacy. Correlations between g and life outcomes are pervasive, though IQ does not correlate with subjective self-reports of happiness. IQ and g correlate highly with school performance and job performance, less so with occupational prestige, moderately with income, and to a small degree with law-abidingness. IQ does not explain the inheritance of economic status and wealth.

It should be remembered that correlation is not causation.

[edit] Other tests

One study found a correlation of .82 between g and SAT scores.[2] Another correlation of .81 between g and GCSE scores.[3]

Correlations between IQ scores (general cognitive ability) and achievement test scores are reported to be .81 by Deary and colleagues, with the percentage of variance accounted for by general cognitive ability ranging "from 58.6% in Mathematics and 48% in English to 18.1% in Art and Design"[31]

[edit] School performance

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) Wherever it has been studied, children with high scores on tests of intelligence tend to learn more of what is taught in school than their lower-scoring peers. The correlation between IQ scores and grades is about .50. However, this means that they explain only 25% of the variance. Successful school learning depends on many personal characteristics other than intelligence, such as persistence, interest in school, and willingness to study.

Correlations between IQ scores and total years of education are about .55, implying that differences in psychometric intelligence account for about 30% of the outcome variance. Many occupations can only be entered through professional schools which base their admissions at least partly on test scores: the MCAT, the GMAT, the LSAT, etc. Individual scores on admission-related tests such as these are certainly correlated with scores on tests of intelligence. It is partly because intelligence test scores predict years of education that they also predict occupational status, and income to a smaller extent.

[edit] Job performance

According to Schmidt and Hunter, "for hiring employees without previous experience in the job the most valid predictor of future performance is general mental ability."[32] The validity of cognitive ability for job performance tends to increase with job complexity and varies across different studies, ranging from 0.2 for unskilled jobs to 0.6 for the most complex jobs.[33]

A meta-analysis (Hunter and Hunter, 1984)[34] which pooled validity results across many studies encompassing thousands of workers (32,124 for cognitive ability), reports that the validity of cognitive ability for entry-level jobs is 0.54, larger than any other measure including job tryout (0.44), experience (0.18), interview (0.14), age (−0.01), education (0.10), and biographical inventory (0.37). This implies that, across a wide range of occupations, intelligence test performance accounts for some 29% of the variance in job performance.

According to Marley Watkins and colleagues, IQ is a casual influence on future academic achievement, whereas academic achievement does not substantially influence future IQ scores.[35] Treena Eileen Rohde and Lee Anne Thompson write that general cognitive ability but not specific ability scores predict academic achievement, with the exception that processing speed and spatial ability predict performance on the SAT math beyond the effect of general cognitive ability.[36]

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that other individual characteristics such as interpersonal skills, aspects of personality, etc., are probably of equal or greater importance, but at this point we do not have equally reliable instruments to measure them.[37]

[edit] Income

Relation between IQ and earnings in the U.S.
IQ <75 75–90 90–110 110–125 >125
Age 18 2,000 5,000 8,000 8,000 ?,000
Age 26 3,000 10,000 16,000 20,000 21,000
Age 32 5,000 12,400 20,000 27,000 36,000
Values are the average earnings (1993 US Dollars) of each IQ sub-population.[38]

One study found that, controlling for IQ across the entire population, 90 to 95 percent of economic inequality would continue to exist.[39]

Some researchers have echoed the popular claim that "in economic terms it appears that the IQ score measures something with decreasing marginal value. It is important to have enough of it, but having lots and lots does not buy you that much."[40][41]

However, some studies suggest IQ continues to confer significant benefits even at very high levels.[42] Ability and performance for jobs are linearly related, such that at all IQ levels, an increase in IQ translates into a concomitant increase in performance (Coward and Sackett, 1990). In an analysis of hundreds of siblings, it was found that IQ has a substantial effect on income independently of family background (Murray, 1998).

A 2002 study instead looked at how much of the correlation between parent and offspring income different factors accounted for. It found that the offspring's inheritance of wealth, inheritance of a high status race, and having received more years of schooling are important factors, but having received a higher IQ is not a major contributor and having received a higher IQ due to genetics is even less important. Regarding policy implications, the authors argue that there are important values of family life and privacy that would be compromised by any serious attempt to disconnect the fortunes of parents and children completely. Instead, a better approach might be to ask which mechanisms of intergenerational transmission seem unfair, and to direct policies accordingly. They argue that the role of race in transmitting economic status from generation to generation is clearly unfair.[43]

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that IQ scores account for about one-fourth of the social status variance and one-sixth of the income variance. Statistical controls for parental SES eliminate about a quarter of this predictive power. Psychometric intelligence appears as only one of a great many factors that influence social outcomes.[44]

One reason why some studies claim that IQ only accounts for a sixth of the variation in income is because many studies are based on young adults (many of whom have not yet completed their education). On pg 568 of The g factor, Arthur Jensen claims that although the correlation between IQ and income averages a moderate 0.4 (one sixth or 16% of the variance), the relationship increases with age, and peaks at middle age when people have reached their maximum career potential. In the book, a Question of Intelligence, Danial Seligman cites an IQ income correlation of 0.5 (25% of the variance).

[edit] Other effects

Economic and social correlates of IQ
Factors Correlation
School grades and IQ 0.5
Total years of education and IQ 0.55
IQ and parental socioeconomic status 0.33
Job performance and IQ 0.54
Negative social outcomes and IQ −0.2
IQs of identical twins 0.86
IQs of husband and wife 0.4
GDP per capita and average national IQ 0.7

In addition, IQ and its correlation to health, violent crime, gross state product, and government effectiveness are the subject of a 2006 paper in the publication Intelligence. The paper breaks down IQ averages by U.S. states using the federal government's National Assessment of Educational Progress math and reading test scores as a source.[45]

There is a correlation of -.19 between IQ scores and number of juvenile offenses in a large Danish sample; with social class controlled, the correlation dropped to -. 17. Similarly, the correlations for most "negative outcome" variables are typically smaller than .20, which means that test scores are associated with less than 4% of their total variance. It is important to realize that the causal links between psychemetric ability and social outcomes may be indirect. Children who are unsuccessful in-and hence alienated from-school may be more likely to engage in delinquent behaviors for that very reason, compared to other children who enjoy school and are doing well.[46]

IQ is also associated with certain diseases.

The book IQ and the Wealth of Nations claims to show that the GDP/person of a nation can in large part be explained by the average IQ score of its citizens. This claim has been both disputed and supported in peer-reviewed papers. The data used have also been questioned.

Tambs et al. (1989) found that occupational status, educational attainment, and IQ are individually heritable; and further found that "genetic variance influencing educational attainment … contributed approximately one-fourth of the genetic variance for occupational status and nearly half the genetic variance for IQ". In a sample of U.S. siblings, Rowe et al. (1997) report that the inequality in education and income was predominantly due to genes, with shared environmental factors playing a subordinate role.

Some argue that IQ scores are used as an excuse for not trying to reduce poverty or otherwise improve living standards for all. Claimed low intelligence has historically been used to justify the feudal system and unequal treatment of women (but note that many studies find identical average IQs among men and women; see sex and intelligence). In contrast, others claim that the refusal of "high-IQ elites" to take IQ seriously as a cause of inequality is itself immoral.[47]

[edit] Public policy

In the United States, certain public policies and laws regarding employment, military service, education and crime incorporate IQ or similar measurements. Internationally, certain public policies, such as improving nutrition and prohibiting neurotoxic toxins, have as one of their goals raising or preventing a decline in intelligence.

[edit] The view of the American Psychological Association

In response to the controversy surrounding The Bell Curve, the American Psychological Association's Board of Scientific Affairs established a task force to write a consensus statement on the state of intelligence research which could be used by all sides as a basis for discussion. The full text of the report is available at a third-party website.[48]

The findings of the task force state that IQ scores do have high predictive validity for individual differences in school achievement. They confirm the predictive validity of IQ for adult occupational status, even when variables such as education and family background have been statistically controlled. They agree that individual (but specifically not population) differences in intelligence are substantially influenced by genetics.

They state there is little evidence to show that childhood diet influences intelligence except in cases of severe malnutrition. They agree that there are no significant differences between the average IQ scores of males and females. The task force agrees that large differences do exist between the average IQ scores of blacks and whites, and that these differences cannot be attributed to biases in test construction. While they admit there is no empirical evidence supporting it, the APA task force suggests that explanations based on social status and cultural differences may be possible. Regarding genetic causes, they noted that there is not much direct evidence on this point, but what little there is fails to support the genetic hypothesis.

The APA journal that published the statement, American Psychologist, subsequently published eleven critical responses in January 1997, most arguing that the report failed to examine adequately the evidence for partly-genetic explanations.

The report was published in 1995 and thus does not include a decade of recent research.

[edit] Criticism

[edit] The Mismeasure of Man

Some scientists dispute psychometrics entirely. In The Mismeasure of Man professor Stephen Jay Gould argued that intelligence tests were based on faulty assumptions and showed their history of being used as the basis for scientific racism. He wrote:

…the abstraction of intelligence as a single entity, its location within the brain, its quantification as one number for each individual, and the use of these numbers to rank people in a single series of worthiness, invariably to find that oppressed and disadvantaged groups—races, classes, or sexes—are innately inferior and deserve their status. (pp. 24–25)

He spent much of the book criticizing the concept of IQ, including a historical discussion of how the IQ tests were created and a technical discussion of why g is simply a mathematical artifact. Later editions of the book included criticism of The Bell Curve.

Gould does not dispute the stability of test scores, nor the fact that they predict certain forms of achievement. He does argue, however, that to base a concept of intelligence on these test scores alone is to ignore many important aspects of mental ability.

Professor Arthur Jensen responded to Gould's criticisms in a paper titled The Debunking of Scientific Fossils and Straw Persons.[49]

[edit] Relation between IQ and intelligence

See also: Intelligence

Several other ways of measuring intelligence have been proposed.

[edit] Test bias

See also: Stereotype threat

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that that IQ tests are not biased against African Americans since they predict future performance, such as school achievement, similarly to the way they predict future performance for whites.[50]

However, IQ tests may well be biased when used in other situations. A 2005 study finds some evidence that the WAIS-R is not culture-fair for Mexican Americans.[51] Other recent studies have questioned the culture-fairness of IQ tests when used in South Africa.[52][53] A recent review also questioned the validity of IQ testing of autistic people.[54]

[edit] Outdated methodology?

A 2006 paper finds that mainstream contemporary test analysis does not reflect substantial recent developments in the field and "bears an uncanny resemblance to the psychometric state of the art as it existed in the 1950s." This applies to many areas of mainstream experimental and quasi-experimental research, such as research on personality, attitudes, cognitive development, and intelligence. For example, it notes that some of the most influential recent studies on group differences in intelligence, in order to show that the tests are unbiased, use outdated methodology, if anything indicative of that test bias exist. It also states that "psychological testing also has a significant and direct impact on people’s lives—for instance, through the use of tests in psychiatric diagnoses or for the selection of employees—and at present such applications do not always stand on firm grounds, to say the least. Thus, we face a pressing obligation to improve the practice of psychological research, and this obligation is not merely of a scientific nature."[55]

[edit] Notes

  1. ^ Jensen, A.R. (1979)
  2. ^ Neisser et al. (1995-08-07). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  3. ^ Linda S. Gottfredson (1998-11). The General Intelligence Factor. Scientific American. Retrieved on August 6, 2006.
  4. ^ R. Plomin, N. L. Pedersen, P. Lichtenstein and G. E. McClearn (05 1994). "Variability and stability in cognitive abilities are largely genetic later in life". Behavior Genetics 24 (3). Retrieved on 2006-08-06.
  5. ^ Plomin et al. (2001, 2003)
  6. ^ Neisser et al. (August 7, 1995). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  7. ^ Thomas J. Bouchard Jr.; David T. Lykken; Matthew McGue; Nancy L. Segal; Auke Tellegen (October 12, 1990). Minnesota Study of Twins Reared Apart. National Institutes of Health / Science, Oct 12, 1990 v250 n4978 p223(6). Retrieved on August 6, 2006.
  8. ^ http://dx.doi.org/10.1007/s10519-007-9142-7
  9. ^ Neisser et al. (August 7, 1995). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  10. ^ Neisser et al. (August 7, 1995). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  11. ^ Neisser et al. (August 7, 1995). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  12. ^ See: Ethnic Differences in Children's Intelligence Test Scores: Role of Economic Deprivation, Home Environment, and Maternal Characteristics
  13. ^ Neisser et al. (August 7, 1995). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  14. ^ Genetic and environmental influences on adult intelligence and special mental abilities. Human Biology, 70, 257–279. 1998
  15. ^ Plomin et al. (2001, 2003)
  16. ^ Neisser et al. (August 7, 1995). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  17. ^ David L. Kirp (July 23, 2006). After the Bell Curve. New York Times Magazine. Retrieved on August 6, 2006.
  18. ^ Stoolmiller, M. (1999). Implications of the restricted range of family environments for estimates of heritability and nonshared environment in behavior-genetic adoption studies. Psychological Bulletin, 125, 392-409.
  19. ^ http://dx.doi.org/10.1007/s10519-007-9142-7
  20. ^ Socioeconomic status modifies heritability of iq in young children Eric Turkheimer, Andreana Haley, Mary Waldron, Brian D'Onofrio, Irving I. Gottesman. Psychological Science 14 (6), 623–628. 2003
  21. ^ New Thinking on Children, Poverty & IQ November 10, 2003 Connect for Kids
  22. ^ The heritability of IQ. Devlin B, Daniels M, Roeder K. Nature. 1997 Jul 31;388(6641):417-8.
  23. ^ DOI:10.1002/neu.10160
  24. ^ DOI:10.1002/neu.10160
  25. ^ William T. Dickens and James R. Flynn, Heritability Estimates Versus Large Environmental Effects:The IQ Paradox Resolved, Psychological Review 2001. Vol. 108, No. 2. 346-369.
  26. ^ William T. Dickens and James R. Flynn, "The IQ Paradox: Still Resolved," Psychological Review 109, no. 4 (2002).
  27. ^ Phillip McClean (1997,1999). Estimating the Offspring Phenotype. Quantitative Genetics. Retrieved on August 6, 2006.
  28. ^ Steve Sailer (June 24, 2002). IQ Defenders Feel Vindicated by Supreme Court. UPI. Retrieved on August 6, 2006.
  29. ^ Coleen A. Boyle, et.al. (April 19, 1996). Prevalence of Selected Developmental Disabilities in Children 3-10 Years of Age: the Metropolitan Atlanta Developmental Disabilities Surveillance Program, 1991. National Center for Environmental Health, Division of Birth Defects and Developmental Disabilities. Retrieved on August 6, 2006.
  30. ^ Olness, K. "Effects on brain development leading to cognitive impairment: a worldwide epidemic," Journal of Developmental and Behavioral Pediatrics 24, no. 2 (2003): 120–30.
  31. ^ Ian J. Deary, Steve Strand, Pauline Smith and Cres Fernandes, Intelligence and educational achievement, Intelligence, Volume 35, Issue 1, January-February 2007, Pages 13-21.
  32. ^ Schmidt, F. L. and Hunter, J. E. (1998). The validity and utility of selection methods in psychology: practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124, 262–274.
  33. ^ Hunter, J. E. and Hunter, R. F. (1984). Validity and utility of alternative predictors of job performance. Psychological Bulletin, 96, 72–98.
  34. ^ Hunter, J. E. and Hunter, R. F. (1984). Validity and utility of alternative predictors of job performance. Psychological Bulletin, 96, 72–98.
  35. ^ Marley W. Watkins, Pui-Wa Lei and Gary L. Canivez, Psychometric intelligence and achievement: A cross-lagged panel analysis, Intelligence, Volume 35, Issue 1, January-February 2007, Pages 59-68.
  36. ^ Treena Eileen Rohde and Lee Anne Thompson, Predicting academic achievement with cognitive ability, Intelligence, Volume 35, Issue 1, January-February 2007, Pages 83-92.
  37. ^ Neisser et al. (August 7, 1995). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  38. ^ Murray, C. (1997). IQ and economic success. Public Interest, 128, 21–35.
  39. ^ IQ best predicts if you will succeed or fail in life. Retrieved on August 6, 2006.
  40. ^ Detterman and Daniel, 1989.
  41. ^ Earl Hunt. The Role of Intelligence in Modern Society 4 (Nonlinearities in Intelligence). American Scientist. Retrieved on August 6, 2006.
  42. ^ Top1in10000.pdf (PDF). Retrieved on August 6, 2006.
  43. ^ The Inheritance of Inequality Bowles, Samuel; Gintis, Herbert. The Journal of Economic Perspectives. Volume 16, Number 3, 1 August 2002, pp. 3-30(28)
  44. ^ Neisser et al. (August 7, 1995). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  45. ^ Michael A. McDaniel, Virginia Commonwealth University (accepted for publication August 2006). Estimating state IQ: Measurement challenges and preliminary correlates (PDF). Intelligence.
  46. ^ Neisser et al.. Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  47. ^ Steve Sailer. How to Help the Left Half of the Bell Curve. VDARE.com. Retrieved on August 6, 2006.
  48. ^ Neisser et al. (August 7, 1995). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  49. ^ Jensen, Arthur (1982). "The Debunking of Scientific Fossils and Straw Persons". Contemporary Education Review 1 (2): 121-135. Retrieved on 2007-03-01.
  50. ^ Neisser et al. (August 7, 1995). Intelligence: Knowns and Unknowns. Board of Scientific Affairs of the American Psychological Association. Retrieved on August 6, 2006.
  51. ^ Culture-Fair Cognitive Ability Assessment Steven P. Verney Assessment, Vol. 12, No. 3, 303-319 (2005)
  52. ^ Cross-cultural effects on IQ test performance: a review and preliminary normative indications on WAIS-III test performance. Shuttleworth-Edwards AB, Kemp RD, Rust AL, Muirhead JG, Hartman NP, Radloff SE. J Clin Exp Neuropsychol. 2004 Oct;26(7):903-20.
  53. ^ Case for Non-Biased Intelligence Testing Against Black Africans Has Not Been Made: A Comment on Rushton, Skuy, and Bons (2004) 1*, Leah K. Hamilton1, Betty R. Onyura1 and Andrew S. Winston International Journal of Selection and Assessment Volume 14 Issue 3 Page 278 - September 2006
  54. ^ "Many times, if the researchers had a child they couldn't test, they just assumed he or she was retarded and assigned a low IQ score." Professor challenges autism assumption. The Oregonian, November 25, 2006.[1]. Retrieved 2007-02-25.
  55. ^ The attack of the psychometricians. DENNY BORSBOOM. PSYCHOMETRIKA VOL 71, NO 3, 425–440. SEPTEMBER 2006.

[edit] See also

[edit] References

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[edit] External links

[edit] Collective statements

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