Bell Curve

768 Notes to pages 569-579 Notes to pages 583-59 1 7693. Data for 1991 had become available in time to be used for the analysis, butfor budgetary reasons, the NLSY had to cut the supplementary sample oflow-income whites as of 1991. We decided that the advantages of includinglow-income whites in the analysis outweighed the advantages of an additionalyear of data.4. We followed the armed forces' convention of limiting suhtest scores to amaximum of three standard deviations from the mean. We gratefullyacknowledge the assistance of Dr. Malcolm J. Ree, who led the rev~sion ofthe AFQT, in computing the revised scores for the NLSY.5. This procedure is facilitated by the large sample sizes (at least 1,265 wlthvalid AFQT scores in each birth year, which are as large as the samplescommonly used for national norms m tests such as the WISC and WAIS),and the fact that the NLSY sample was balanced for ethnic group and genderwithin birth years.6. We also experimented with groupings based not on the calendar year, hutthe school year. The differences in centile produced by the two procedureswere never as much as two, so we remained with calendar year as the hasis.7. See Users Guide 1993, pp. 157-162.Appendix 31. The subtests are General Science (GS), Arithmetic Reasoning (AR),Work Knowledge (WK), Paragraph Comprehension (PC), Numerical Operations(NO), Coding Speed (CS), Auto/Shop Information (AS), MathematicsKnowledge (MK), Mechanical Comprehension (MC), andElectronics Information (EL). Two subtests (Numerical Operations andCoding Speed) are highly speeded; the other eight are "power" rather thanspeed tests.2. Ree and Earles 1990a, 1990b, 1991c.3. We use the term factor in a generic sense. Within psychometrics, termslike factor and component are used selectively, depending on the particularmethod of analysis used to extract the measures.4. E.g., Could 1981.5. Jensen 1987a, 1987b; Ree and Earles 1991c; Welsh, Watson, and Ree 1990.6. To account for literally 100 percent of the variance takes ten factors (hecausethere are ten subtests), with the final few of them making increasinglynegligible contributions. In the case of ASVAR, the final five factorscollectively account for only 10 percent of the total variance in scores.7. Sperl, Ree and Steuck 1990.8. Carroll 1988; Jensen 1987a.9. Ree and Earles, 1990a, 1990b, 1991c.10. Gordon 1984; Jensen and Figueroa 1975.11, Note that the General Science subtest and the Electronics Informationsubtest are as highly g-loaded as the subtests used in the AFQT. Why notuse them as well! Because they draw on knowledge that is specific to certaincourses that many youths might not have taken, whereas the mathematicsand reading subtests require only material that is ordinarily coveredin the courses taken by every student who goes to elementary and secondaryschool. Rut this is a good illustration of a phenomenon associatedwith IQ tests: People who acquire knowledge about electronics and sciencealso tend to have high mathematics and verbal ability.12. Jensen 1980, Table 6.10.13. Within a single test, the test score might mean any of several percentilescores, depending on the age of the student; hence the reason for using percentiles.For the analyses in the text, scores were used only if both a testscore and a percentile were recorded. Anomalous scores were discarded asfollows: For the California Test of Mental Maturity, one test score of 700.For the Otis-Lennon Mental Ability Test, eight cases in which the testscore was under 30 and the percentile was over 70; one case in which thetest score was 176 and the percentile was only 84. For the Henmon-NelsonTest of Mental Maturity, one test score of 374. For the DifferentialAptitude Test, sixteen test scores over 100. For the Lorge-Thomdtke IntelligenceTest and the Kuhlmann-Anderson Intelligence Test, w h~hshowed uninterpretable scatter plots of test scores against percentiles, caseswere retained if the test score normed according to a mean of 100 and astandard deviation of 15 was within 10 centiles of the reported percentilescore. The number of eligible scores on the Stanford-Binet and the WechslerIntelligence Scale for Children (18 and 16, respectively) was too smallto analyze.14. Jensen 1980, Table 8.5.15. This list is taken from Jensen 1980, p. 72. Jensen devotes a chapter (Chap.4) to the distribution of mental ability, which we recommend as an excellentsingle source for readers who want to pursue this issue.16. For an exploration of the relationships as of the late 1960s, see Jencks etal. 1972, Appendix B. For separate studies, see Rutter 1985; Hale, Raymond,and Gajar 1982; Wolfe 1982; Schiff and Lewontin, 1986.17. Hustn and Tuijnman, 1991. See also Ceci 1991, for a case that schoolinghas a greater influence on IQ than has generally been accepted, drawingheavily on data from earlier decades when the natural variation in schoolingwas large.