Hostname: page-component-7479d7b7d-qs9v7 Total loading time: 0 Render date: 2024-07-11T22:01:20.789Z Has data issue: false hasContentIssue false
  • English
  • Français

I've Found It, but What Does It Mean? On the Importance of Theory in Identifying Dominant General Factors

Published online by Cambridge University Press:  23 March 2016

Zhenyu Yuan
Zhenyu Yuan*
Affiliation:
Department of Management and Organizations, University of Iowa
*
Correspondence concerning this article should be addressed to Zhenyu Yuan, Department of Management and Organizations, University of Iowa, 108 John Pappajohn Business Building, Iowa City, IA 52242. E-mail: zhenyu-yuan@uiowa.edu
Get access Rights & Permissions [Opens in a new window]

Extract

In their focal article, Ree, Carretta, and Teachout (2015) based their definition of a dominant general factor (DGF) on two criteria: (a) A DGF should be the largest source of reliable variance; (b) it is influencing every variable measuring the construct. Although detailed attention has been paid to the statistical properties of a DGF, I believe another criterion of equal if not greater importance is the theoretical justification to expect a DGF in the measurement of a construct. In the following commentary, I will highlight the importance of theory as another important criterion when determining the meaningfulness and usefulness of DGFs, discuss the risks of creating a DGF without any theoretical guidance, and elaborate on the complexities surrounding job performance as a detailed example to illustrate why theory is important before extracting a DGF from performance ratings.

Type
Commentaries
Information
Industrial and Organizational Psychology , Volume 9 , Issue 1 , March 2016 , pp. 212 - 216
Copyright
Copyright © Society for Industrial and Organizational Psychology 2016 

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

Bergeron, D. M., Shipp, A. J., Rosen, B., & Furst, S. A. (2013). Organizational citizenship behavior and career outcomes the cost of being a good citizen. Journal of Management, 39, 958–984.Google Scholar
Campbell, J. P., McCloy, R. A., Oppler, S. H., & Sager, C. E. (1993). A theory of performance. In Schmitt, N. & Borman, W. C. (Eds.), Personnel selection in organizations (pp. 35–70). San Francisco, CA: Jossey-Bass.Google Scholar
Carretta, T. S., Perry, D. C. Jr, & Ree, M. J. (1996). Prediction of situational awareness in F-15 pilots. The International Journal of Aviation Psychology, 6, 21–41.Google Scholar
Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78, 98–104.Google Scholar
Edwards, J. R. (2001). Multidimensional constructs in organizational behavior research: An integrative analytical framework. Organizational Research Methods, 4, 144–192.Google Scholar
Edwards, J. R., & Bagozzi, R. P. (2000). On the nature and direction of relationships between constructs and measures. Psychological Methods, 5, 155–174.Google Scholar
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272–299.Google Scholar
Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1, 104–121.Google Scholar
Judge, T. A., Erez, A., Bono, J. E., & Thoresen, C. J. (2003). The core self-evaluations scale: Development of a measure. Personnel Psychology, 56, 303–331.Google Scholar
Judge, T. A., Locke, E. A., & Durham, C. C. (1997). The dispositional causes of job satisfaction: A core evaluations approach. Research in Organizational Behavior, 19, 151–188.Google Scholar
Lance, C. E., Teachout, M. S., & Donnelly, T. M. (1992). Specification of the criterion construct space: An application of hierarchical confirmatory factor analysis. Journal of Applied Psychology, 77, 437–452.Google Scholar
Law, K. S., Wong, C. S., & Mobley, W. H. (1998). Toward a taxonomy of multidimensional constructs. Academy of Management Review, 23, 741–755.CrossRefGoogle Scholar
Murphy, K. R., & Shiarella, A. H. (1997). Implications of the multidimensional nature of job performance for the validity of selection tests: Multivariate frameworks for studying test validity. Personnel Psychology, 50, 823–854.Google Scholar
Packer, E. (1985a). Understanding the subconscious (I). The Objectivist Forum, 6 (1), 1–10.Google Scholar
Packer, E. (1985b). Understanding the subconscious (II). The Objectivist Forum, 6 (2), 8–15.Google Scholar
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, 409–427.Google Scholar
Spector, P. E. (2006). Method variance in organizational research truth or urban legend? Organizational Research Methods, 9, 221–232.Google Scholar
Viswesvaran, C., Schmidt, F. L., & Ones, D. S. (2005). Is there a general factor in ratings of job performance? A meta-analytic framework for disentangling substantive and error influences. Journal of Applied Psychology, 90, 108–131.Google Scholar
Wallace, C., & Chen, G. (2006). A multilevel integration of personality, climate, self-regulation, and performance. Personnel Psychology, 59, 529–557.CrossRefGoogle Scholar