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Managing the First Factor: Context Is Important

Published online by Cambridge University Press:  02 October 2015

Anne Thissen-Roe*
Affiliation:
Comira, San Mateo, California
Michael S. Finger
Affiliation:
Comira, San Mateo, California
Pamela G. Ing
Affiliation:
Comira, San Mateo, California
*
Correspondence concerning this article should be addressed to Anne Thissen-Roe, Comira, 777 Mariners Island Boulevard, Suite 200, San Mateo, CA 94404. E-mail: athissenroe@comiratesting.com

Extract

In the focal article, Ree, Carretta, and Teachout (2015) address a common error in research methods, in which researchers neglect the shared variance between facets of a multidimensional construct. We agree with the need to attend to the entire factor structure of constructs when using measures, whether in research or application. The objective of this commentary is to elaborate on useful practices when a dominant general factor (DGF), as defined by the focal article, is found to be present and, in particular, to explore cases of DGF results under research paradigms not considered by the focal article.

Type
Commentaries
Copyright
Copyright © Society for Industrial and Organizational Psychology 2015 

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References

Campbell, J. P., McCloy, R. A., Oppler, S. H., & Sager, C. E. (1993). A theory of performance. In Schmidt, N., Borman, W. C., & Associates (Eds.), Personnel selection in organizations (pp. 3570), San Francisco, CA: Jossey-Bass.Google Scholar
Carroll, J. B. (1993). Human cognitive abilities: A survey of factor-analytic studies. Cambridge, MA: Cambridge University Press.Google Scholar
McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah, NJ: Erlbaum.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 (3), 409427.Google Scholar
Reise, S. P., Moore, T. M., & Haviland, M. G. (2010). Bifactor models and rotations: Exploring the extent to which multidimensional data yield univocal scale scores. Journal of Personality Assessment, 92 (6), 544559.CrossRefGoogle ScholarPubMed
Sinharay, S., & Puhan, G. (2007). Subscores based on classical test theory: To report or not to report. Educational Measurement: Issues and Practice, 26, 2128.Google Scholar
Stout, W. F. (1990). A new item response theory modeling approach with applications to unidimensionality assessment and ability estimation. Psychometrika, 55 (2), 293325.Google Scholar
Thissen, D. (2013). Using the testlet response model as a shortcut to multidimensional item response theory subscore computation. In Millsap, R. E., van der Ark, L. A., Bolt, D. M., & Woods, C. M. (Eds.), New developments in quantitative psychology—Presentations from the 77th Annual Psychometric Society Meeting (pp. 2940). New York, NY: Springer.Google Scholar
Tukey, J. W. (1973). Exploratory data analysis as part of a large whole. In Proceedings of the eighteenth conference on the design of experiments in Army research, development and testing, Part I (pp. 110). Durham, NC: Army Research Office.Google Scholar
Wainer, H., & Lewis, C. (1990). Towards a psychometrics for testlets. Journal of Educational Measurement, 27 (1), 114.Google Scholar