SAT and ACT predict college GPA after removing g

Intelligence

Volumn 36, Issue 6, 2008, Pages 719-729

  Coyle, Thomas R ^a   Pillow, David R ^a  

^a UNIVERSITY OF TEXAS AT SAN ANTONIO   (United States)

Author keywords

ACT; Armed Services Vocational Aptitude Battery; ASVAB; g factor; GPA; Grade point average; Intelligence; IQ; National Longitudinal Study of Youth; NLSY; SAT; SEM; Structural equation modeling

Indexed keywords

EID: 53849117070     PISSN: 01602896     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.intell.2008.05.001     Document Type: Article

References (28)

1. Bridgeman B., McCamley-Jenkins L., and Ervin N. Predictions of freshman grade-point average from the revised and recentered SAT I: reasoning test (College Board Report No. 2000-1) (2000), College Entrance Examination Board, New York
2. Brodnick R.J., and Ree M.J. A structural model of academic performance, socioeconomic status, and Spearman's g. Educational and Psychological Measurement 55 (1995) 583-594
3. Browne M.W., and Cudeck R. Alternative ways of assessing model fit. In: Bollen K.A., and Long J.S. (Eds). Testing structural equation models (1993), Sage, Newbury Park, CA 136-162
4. Cohen J. Statistical power analysis for the behavioral sciences. (2nd ed.) (1988), Erlbaum, Mahwah, NJ
5. Coyle T.R. Test-retest changes on scholastic aptitude tests are not related to g. Intelligence 34 (2006) 15-27
6. Dorans N.J. Correspondences between ACT and SAT I scores (College Board Report No. 99-1) (1999), College Entrance Examination Board, New York
7. Enders C.K., and Bandalos D.L. The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Structural Equation Modeling 8 (2001) 430-457
8. Frey M.C., and Detterman D.K. Scholastic assessment or g? The relationship between the Scholastic Assessment Test and general cognitive ability. Psychological Science 15 (2004) 373-378
9. Friedman N.P., and Miyake A. The relations among inhibition and interference control functions: A latent-variable analysis. Journal of Experimental Psychology: General 133 (2004) 101-135
10. Hu L.-T., and Bentler P.M. Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling 6 (1999) 1-55
11. Jensen A.R. The g factor: the science of mental ability (1998), Praeger, Westport, CT
12. Johnson W., Bouchard T.J., Krueger R.F., McGue M., and Gottesman I.I. Just one g: Consistent results from three test batteries. Intelligence 32 (2004) 95-107
13. Johnson W., te Nijenhuis J., and Bouchard Jr. T.J. Still just 1 g: Consistent results from five test batteries. Intelligence 36 (2008) 81-95
14. Kline R.B. Principles and practice of structural equation modeling. (2nd ed.) (2005), New York, Guildford
15. Kobrin J.L., and Schmidt A.E. The research behind the new SAT (College Board Research Summary RS-11) (2005), College Entrance Examination Board, New York
16. Koenig K.A., Frey M.C., and Detterman D.K. ACT and general cognitive ability. Intelligence 36 (2008) 153-160
17. Kuncel N.R., Credé M., and Thomas L.L. The validity of self-reported grade point averages, class ranks, and test scores: A meta-analysis and review of the literature. Review of Educational Research 75 (2005) 63-82
18. Marshalek B., Lohman D.F., and Snow R.E. The complexity continuum in the radex and hierarchical models of intelligence. Intelligence 7 (1983) 107-127
19. Moutafi J., Furnham A., and Crump J. What facets of openness and conscientiousness predict fluid intelligence score?. Learning and Individual Differences 16 (2006) 31-42
20. Noble J. Effects of differential prediction in college admissions for traditional and nontraditional-aged students (ACT Research Report Series 2000-9) (2000), ACT, Iowa City, IA
21. O'Connor M.C., and Paunonen S.V. Big Five personality predictors of post-secondary academic performance. Personality and Individual Differences 43 (2007) 971-990
22. Park G., Lubinski D., and Benbow C.P. Contrasting intellectual patterns predict creativity in the arts and sciences: Tracking intellectually precocious youth over 25 years. Psychological Science 18 (2007) 948-952
23. Reddy S.K. Effects of ignoring correlated measurement errors in structural equation models. Educational and Psychological Measurement 52 (1992) 549-570
24. Schmidt F.L., and Hunter J.E. The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin 124 (1998) 262-274
25. Stinebrickner T.R., and Stinebrickner R. The causal effect of studying on academic performance (NBER Working Paper No. 13341) (2007), National Bureau of Economic Research, Cambridge, MA
26. UTSA Fact Book (n.d.). Retrieved August 22, 2007, from the University of Texas at San Antonio, Office of Institutional Research Web site: http://www.utsa.edu/ir/Factbook/Fact_Book_2006.pdf
27. Wechsler D. WAIS-III administration and scoring manual (1997), The Psychological Corporation, San Antonio, TX
28. Wonderlic. Wonderlic personnel test and scholastic level exam: user's manual (1999), Wonderlic, Inc, Libertyville, IL