General Mental Ability aka (GMA) aka (g factor) aka (g)

1. General Mental Abilityaka (GMA)aka (g factor)aka (g) John Breidert & James Hellrung

2. GMA Haiku General Mental Tests One Concept With Many Parts Test the “g factor”

3. Overview • Introduction into GMA and Supporting Theories • GMA on the job and in tests

4. Introduction into GMA and Supporting Theories • Introduction to General Mental Ability • Spearman’s Two-factor Theory of Intelligence • Vernon’s Hierarchical Theory of Intelligence • Carroll’s Three-Stratum Factor Analytic Theory of Cognitive Abilities

5. Introduction to General Mental Ability • General Mental Ability is the sum of many parts of intelligence • Building Example

6. Spearman’s Two-factor Theory of Intelligence • Spearman (1863- 1945) Proposed the theory in 1927 • General Factor (g) in addition to one or more specific factors accounted for people’s performance on intelligence tests • Spearman saw the g factor as a mental energy that was expended on different mental tasks • Spearman saw the g factor as more of the inventive aspect of mental ability

7. Spearman’s Two-factor Theory of Intelligence

8. Vernon’s Hierarchical Theory of Intelligence • Philip E. Vernon (1950) • Hierarchical theory of intelligence • g at highest level, must consider it in order to understand or measure intelligence • At next level are the major group factors: • Verbal-Educational • Spatial-Mechanical

9. Vernon’s Hierarchical Theory of Intelligence • Next level is minor group factors: • Lowest level contains specialized factors that are unique to specific tests • Therefore, the lower on the hierarchy, the most specific the behavior • Vernon’s theory is supported by numerous studies finding positive intercorrelations among different tests

10. Vernon’s Hierarchical Theory of Intelligence

11. Carroll’s Three-Stratum Factor Analytic Theory of Cognitive Abilities • John B. Carroll (1993) proposed a three stratum factor analytic theory of cognitive abilities • There are many distinct differences in cognitive ability

12. Carroll’s Three-Stratum Factor Analytic Theory of Cognitive Abilities • Narrow (stratum 1) • 65 narrow abilities • Level factors • Speed factors • Rate factors • Broad (stratum 2) • 8 broad factors • General (stratum 3) • Consists of only g

13. Carroll’s Three-Stratum Factor Analytic Theory of Cognitive Abilities

14. GMA on the Job and in Tests • GMA and Occupational Level • GMA and Job Performance • GMA and Training Performance • Other Traits and Variables Affecting Job Performance • Group Differences for GMA • General Reactions to GMA • New Methods of Testing GMA

15. GMA and Occupational Level • Cross-sectional & Longitudinal Studies relate GMA to occupational level • Cross-sectional Studies – mean GMA increases with occupational level • Longitudinal Studies – GMA measured earlier in life predicts later occupational level. • Job mobility predicted by congruence between peoples’ GMA scores and complexity of their job • Childhood GMA predicts adult occupation level (r = .51) and income (r = .53) • GMA predicts attained job level, but not which occupation within that level

16. GMA and Job Performance • GMA used for predicting Job Performance since WWI • Situational Specificity theory says GMA predicts job performance sporadically • Validity coefficients varied across studies • Some statistically significant, some not • Truth – variability in validity findings due to statistical and measurement artifacts. • After correcting for effects of artifacts, there was little variability in validity, and GMA measures were predictive of job performance for all jobs.

17. GMA and Job Performance • Validity ranges • .58 for most complex jobs • .23 for least complex jobs • Validity for job performance shown in many studies: • Clerical jobs - .52 (Pearlman, Schmidt, & Hunter, 1980) • Law Enforcement - .38 ( Hirsh, Northrup, & Schmidt (1986) • Military “Core Technical Proficiency” - .63 (McHenry et al., 1990) • Military “General Soldiering Proficiency” - .65 (McHenry et al., 1990) • Air Force jobs – mean of .45 (Ree, Earles & Teachout, 1994)

18. GMA and Training Performance • Validity for training performance also: • Meta-analysis of 90 studies - > .50 (Hunter & Hunter, 1984) • Military meta-analysis of over 82,000 trainees - > .63 (Hunter, 1986) • Air Force meta-analysis of over 77,958 trainees - > .60 (Ree & Earles, 1991) • Clerical workers – mean of .71 (Pearlman et al., 1980) • Law enforcement – mean value of .76 (Hirsh et al., 1986) • Across meta analyses, unweighted average validity: • .55 for job performance • .63 for training performance

19. Other Traits and Variables Affecting Job Performance • Specific Aptitudes • Cognitive abilities narrower than GMA • Regression equations optimize prediction of job and training performance • Disconfirmed - Causal analysis modeling failed to fit the data, but a hierarchical model fit well (Hunter, 1983b) • Use of specific aptitudes may reduce group differences • Job Experience • More job experience, not GMA should predict job performance • As experience increases, predictive validity of GMA does not decrease. • Actually goes from .36 for 0-6 years to .44 for 6-12 years, up to .59 for more than 12 years. • If anything, as experience increases, so does validity of GMA

21. Other Traits and Variables Affecting Job Performance • Personality Traits • Predicted occupational level and income (Judge et al., 1999) • Conscientiousness : .49 and .41 • Openness to experience: .32 and .26 • Neuroticism: -.26 and -.34 • GMA: .51 and .53 • When placed career success in regression equation: • Multiple r = .63 • Neuroticism: β = -.05 • Openness: β = -.03 • Conscientiousness: β = .27 • GMA: β = .43 • When only Conscientiousness and GMA in equation: • Multiple r = .63 • Conscientiousness is only personality trait contributing to career success

22. Group Differences for GMA • Specific aptitudes have smaller group differences • May be due to unreliability and range restriction • However GMA tests are more reliable than other predictors • GMA produces racial differences • 3-5 times more difference than produced by interviews, biodata, and work sample tests. • Could be due to measurement error in the above • Four-fifths rule • Infers adverse impact when selection rate for the low-scoring group < 4/5 the selection rate for the high-scoring group • Because job complexity increases the likelihood of adverse impact, Viswesvaran & Ones (2002) suggest a sliding adverse impact rule (e.g., .50 for complex jobs and .80 for simple ones) • GMA is a best predictor of job performance, but also predictor with most adverse impact

23. General Reactions to GMA • Even students who are not aware of group differences have negative reactions • In homogenous societies, there are also negative reactions to GMA (Viswesvaran & Ones, 2002) • Past abuses of testing for GMA still haunt us • Research on applicant reactions to GMA needs to continue, but still at its infancy • Laypeople maybe convince that cognitive ability is not important in determining intelligent behavior. • Although research suggests validity of GMA increases with increased job complexity, organizations are less likely to use GMA for high-level jobs than lower-level jobs. (Face validity?)

24. New Methods of Testing GMA • Low cost of paper & pencil • Killed demand for other testing media • To reduce group differences • One strategy is to change test medium • Computerized and video-based assessments • Must be careful not to change construct being measured • Format changes may induce differences in GMA and individual differences in responding to the new medium

25. New Methods of Testing GMA • In the future: • May see tools based on physiological, biological, and genetic markers identified for GMA • Whether they are accepted depends on societal views on privacy rights versus organizational needs • Bottom line – If the use of different mediums reduces adverse impact without reducing validity for a criterion, then the new method is preferred

26. Questions?