Hostname: page-component-77c89778f8-7drxs Total loading time: 0 Render date: 2024-07-23T18:07:24.892Z Has data issue: false hasContentIssue false
  • English
  • Français

There Are More Things in Heaven and Earth, Horatio, Than DGF

Published online by Cambridge University Press:  02 October 2015

Paul J. Hanges ,
Charles A. Scherbaum  and
Charlie L. Reeve
Paul J. Hanges*
Affiliation:
Department of Psychology, University of Maryland
Charles A. Scherbaum
Affiliation:
Department of Psychology, Baruch College, City University of New York
Charlie L. Reeve
Affiliation:
Department of Psychology, University of North Carolina at Charlotte
*
Correspondence concerning this article should be addressed to Paul J. Hanges, Department of Psychology, University of Maryland, College Park, MD 20742. E-mail: phanges@umd.edu
Get access Rights & Permissions [Opens in a new window]

Extract

In their article, Ree, Carretta, and Teachout (2015) argued that a dominant general factor (DGF) is present in most, if not all, psychological measures (e.g., personality, leadership, attitudes, skills). A DGF, according to Ree et al., is identified by two characteristics. First, the DGF accounts for the largest amount of a measure's systematic variance, and second, it influences every subdimension within the construct domain. They indicate that researchers ignore DGFs and pay inappropriate amounts of attention to the specific dimensions (DSs) even though the DGF provides most of the predictive power and the DS adds little predictive power.

Type
Commentaries
Information
Industrial and Organizational Psychology , Volume 8 , Issue 3 , September 2015 , pp. 472 - 481
Copyright
Copyright © Society for Industrial and Organizational Psychology 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ackerman, P. L. (1996). A theory of adult intellectual development: Process, personality, interests, and knowledge. Intelligence, 22 (2), 227–257.Google Scholar
Ashton, M. C., Lee, K., Goldberg, L. R., & de Vries, R. E. (2009). Higher order factors of personality: Do they exist? Personality and Social Psychology Review, 13, 79–91.Google Scholar
Chamorro-Premuzic, T., & Furnham, A. (2005). Personality and intellectual competence. Mahwah, NJ: Erlbaum.Google Scholar
Corno, L., Cronbach, L. J., Kupermintz, H., Lohman, D. F., Mandinach, E. B., . . . Talbert, J. E. (2002). Remaking the concept of aptitude: Extending the legacy of Richard E. Snow. Mahwah, NJ: Erlbaum.Google Scholar
DeYoung, C. G. (2006). Higher-order factors of the Big Five in a multi-informant sample. Journal of Personality and Social Psychology, 91, 1138–1151.CrossRefGoogle Scholar
DeYoung, C. G., Peterson, J. B., & Higgins, D. M. (2002). Higher-order factors of the Big Five predict conformity: Are there neuroses of health? Personality and Individual Differences, 33, 533–552.CrossRefGoogle Scholar
Digman, J. M. (1997). Higher-order factors of the Big Five. Journal of Personality and Social Psychology, 73, 1246–1256.Google Scholar
Donnellan, M. B., Hopwood, C. J., & Wright, A. G. C. (2012). Revaluating the evidence for the general factor of personality in the multidimensional personality questionnaire: Concerns about Rushton and Irwing (2009). Personality and Individual Differences, 52, 285–289.Google Scholar
Ghiselli, E. E., Campbell, J. P., & Zedeck, S. (1981). Measurement theory for the behavioral sciences. San Francisco, CA: Freeman.Google Scholar
Gottfredson, L. (1997). Why g matters: The complexity of everyday life. Intelligence, 24, 79–132.Google Scholar
Gustafsson, J.-E. (2002). Measurement from a hierarchical point of view. In Braun, H. L., Jackson, D. G., & Wiley, D. E. (Eds.), The role of constructs in psychological and educational measurement (pp. 73–95). Mahwah, NJ: Erlbaum.Google Scholar
Hogan, J., & Roberts, B. W. (1996). Issues and non‐issues in the fidelity‐bandwidth trade‐off. Journal of Organizational Behavior, 17, 627–637.Google Scholar
Hopwood, C. J., Wright, A. G. C., & Donnellan, M. B. (2011). Evaluating the evidence for the general factor of personality across multiple inventories. Journal of Research in Personality, 45, 468–478.CrossRefGoogle ScholarPubMed
Hunter, J. E. (1986). Cognitive ability, cognitive aptitudes, job knowledge, and job performance. Journal of Vocational Behavior, 29, 340–362.Google Scholar
Judge, T. A., & Kammeyer-Mueller, J. D. (2012). General and specific measures in organizational behavior research: Considerations, examples, and recommendations for researchers. Journal of Organizational Behavior, 33, 161–174. doi:10.1002/job.764Google Scholar
Kuncel, N. R., & Sackett, P. R. (2014). Resolving the assessment center construct validity problem (as we know it). Journal of Applied Psychology, 99, 38–47.CrossRefGoogle ScholarPubMed
Lang, J. W., Kersting, M., Hülsheger, U. R., & Lang, J. (2010). General mental ability, narrower cognitive abilities, and job performance: The perspective of the nested‐factors model of cognitive abilities. Personnel Psychology, 63, 595–640.Google Scholar
Lievens, F., & Reeve, C. L. (2012). Where I-O psychology should really (re)start its investigation of intelligence constructs and their measurement. Industrial and Organizational Psychology: Perspectives on Science and Practice, 5, 153–158.CrossRefGoogle Scholar
McHenry, J. J., Hough, L. M., Toquam, J. L., Hanson, M. A., & Ashworth, S. (1990). Project A validity results: The relationships between predictor and criterion domains. Personnel Psychology, 43, 335–354.Google Scholar
Mount, M. K., Barrick, M. R., Scullen, S. M., & Rounds, J. (2005). Higher-order dimensions of the Big Five personality traits and the Big Six vocational interest types. Personnel Psychology, 58, 447–478.Google Scholar
Musek, J. (2007). A general factor of personality: Evidence for the Big One in the five-factor model. Journal of Research in Personality, 41, 1213–1233.CrossRefGoogle Scholar
Park, G., Lubinski, D., & Benbow, C. P. (2008). Ability differences among people who have commensurate degrees matter for scientific creativity. Psychological Science, 19, 957–961.Google Scholar
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–569.CrossRefGoogle ScholarPubMed
Ree, M. J., Carretta, T. R., & Teachout, M. S. (2015). Pervasiveness of dominant general factors in organizational measurement. Industrial and Organizational Psychology: Perspectives on Science and Practice, 8 (3), 409–427.Google Scholar
Ree, M. J., & Earles, J. A. (1991). Predicting training success: Not much more than g . Personnel Psychology, 44, 321–332.CrossRefGoogle Scholar
Ree, M. J., Earles, J. A., & Teachout, M. S. (1994). Predicting job performance: Not much more than g. Journal of Applied Psychology, 79, 518–524.CrossRefGoogle Scholar
Reeve, C. L. (2004). Differential ability antecedents of general and specific dimensions of declarative knowledge: More than g. Intelligence, 32, 621–652.Google Scholar
Reeve, C. L., & Hakel, M. D. (2002). Asking the right questions about g. Human Performance, 15, 47–74.Google Scholar
Reeve, C. L., Scherbaum, C. A., & Goldstein, H. W. (2015). Manifestations of intelligence: Expanding the measurement space to reconsider specific cognitive abilities. Human Resource Management Review, 25, 28–37.Google Scholar
Rushton, J. P., Bons, T. A., Ando, J., Hur, Y. M., Irwing, P., Vernon, P. A., . . . Barbaranelli, C. (2009). A general factor model of personality from multitrait-multimethod data and cross-national twins. Twin Research and Human Genetics, 12, 356–365.CrossRefGoogle ScholarPubMed
Rushton, J. P., Bons, T. A., & Hur, Y. M. (2008). The genetics and evolution of the general factor of personality. Journal of Research in Personality, 42, 1173–1185.Google Scholar
Rushton, J. P., & Irwing, P. (2008). A general factor of personality (GFP) from two meta-analyses of the Big Five: Digman (1997) and Mount, Barrick, Scullen, and Rounds (2005). Personality and Individual Differences, 45, 679–683.CrossRefGoogle Scholar
Schneider, W. J., & McGrew, K. S. (2012). The Cattell-Horn-Carroll model of intelligence. In Flanagan, D. & Harrison, P. (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 99–144). New York, NY: Guilford Press.Google Scholar
Schneider, W. J., & Newman, D. A. (2015). Intelligence is multidimensional: Theoretical review and implications of specific cognitive abilities. Human Resource Management Review, 25, 12–27.CrossRefGoogle Scholar
Shea, D. L., Lubinski, D., & Benbow, C. P. (2001). Importance of assessing spatial ability in intellectually talented young adolescents: A 20-year longitudinal study. Journal of Educational Psychology, 93, 604–614.Google Scholar
Snow, R. E. (1987). Aptitude complexes. Aptitude, Learning and Instruction, 3, 11–34.Google Scholar
Snow, R. E. (1992). Aptitude theory: Yesterday, today, and tomorrow. Educational Psychologist, 27 (1), 5–32.Google Scholar
van der Maas, H. L., Dolan, C. V., Grasman, R., Wicherts, J. M., Huizenga, H. M., & Raijmakers, M. (2006). A dynamical model of general intelligence: The positive manifold of intelligence by mutualism. Psychological Bulletin, 113, 842–861.Google ScholarPubMed
Wai, J. (2013). Experts are born, then made: Combining prospective and retrospective longitudinal data shows the cognitive ability matters. Intelligence. doi:10.1016/j.intell.2013.08.009Google Scholar
Webb, R. M., Lubinski, D., & Benbow, C. P. (2007). Spatial ability: A neglected dimension in talent searches for intellectually precocious youth. Journal of Educational Psychology, 99, 397–420.Google Scholar
Wee, S., Newman, D., & Joseph, D. (2014). More than g: Selection quality and adverse impact implications of considering second-stratum cognitive abilities. Journal of Applied Psychology, 99, 547–563.CrossRefGoogle Scholar
Youngstrom, E. A., Kogos, J. L., & Glutting, J. J. (1999). Incremental efficacy of Differential Ability Scales factor scores in predicting individual achievement criteria. School Psychology Quarterly, 14, 26–39.Google Scholar