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Multilevel MethodsFuture Directions in Measurement, Longitudinal Analyses, and Nonnormal Outcomes
Paul D. Bliese
U.S. Army Medical Research Unit-Europe, paul.bliese{at}us.army.mil
David Chan
Singapore Management University, davidchan{at}smu.edu.sg
Robert E. Ployhart
University of South Carolina, Columbia, Ployhart{at}moore.sc.edu
The study of multilevel phenomena in organizations involves a complex interplay between methods and statistics on one hand and theory development on the other. In this introduction, the authors provide a short summary of the five articles in this feature topic and use them as a platform to discuss the broad need for work in the two areas of (a) multilevel construct validation and measurement and (b) statistical advances in variance decomposition. Within these two broad frameworks, the authors specifically discuss, first, the need to continue moving beyond notions of isomorphism in developing and testing aggregate-level constructs. Second, they discuss the potential value of using discontinuous growth models to understand transitions in longitudinal studies. Finally, they discuss some of the issues surrounding the ability to decompose variance in multilevel modeling of dichotomous and other nonnormal outcome data.
Key Words: multilevel • discontinuity • transition • construct validation • agreement
References
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- Bliese, P.D. (2006). Social climates: Drivers of soldier well-being and resilience. In A. B. Adler, C. A. Castro, & T. W. Britt (Eds.), Military life: The psychology of serving in peace and combat: Vol. 2. Operational stress (pp. 213-234). Westport, CT: Praeger.
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- Bliese, P.D., & Ployhart, R.E. (2002). Growth modeling using random coefficient models: Model building, testing, and illustrations. Organizational Research Methods, 5, 362-387.[Abstract]
- Bliese, P.D., Wesensten, N., & Balkin, T.J. (2006). Age and individual variability in performance during sleep restriction. Journal of Sleep Research, 15, 376-385.[CrossRef][Web of Science][Medline]
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This version was published on October
1, 2007
Organizational Research Methods, Vol. 10, No. 4,
551-563 (2007)
DOI: 10.1177/1094428107301102
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