J. Wieseke
Multilevel Analyses in Marketing Research: Differentiating Analytical Outcomes
Wieseke, J.; Broderick, A.J.; Lee, N.; Dawson, J.F.; Van Dick, R.
Authors
A.J. Broderick
N. Lee
J.F. Dawson
R. Van Dick
Abstract
Marketing scholars are increasingly recognizing the importance of investigating phenomena at multiple levels. However, the analyses methods that are currently dominant within marketing may not be appropriate to dealing with multilevel or nested data structures. We identify the state of contemporary multilevel marketing research, finding that typical empirical approaches within marketing research may be less effective at explicitly taking account of multilevel data structures than those in other organizational disciplines. A Monte Carlo simulation, based on results from a previously published marketing study, demonstrates that different approaches to analysis of the same data can result in very different results (both in terms of power and effect size). The implication is that marketing scholars should be cautious when analyzing multilevel or other grouped data, and we provide a discussion and introduction to the use of hierarchical linear modeling for this purpose.
Citation
Wieseke, J., Broderick, A., Lee, N., Dawson, J., & Van Dick, R. (2008). Multilevel Analyses in Marketing Research: Differentiating Analytical Outcomes. Journal of Marketing Theory and Practice, 16(4), 321-340. https://doi.org/10.2753/mtp1069-6679160405
Journal Article Type | Article |
---|---|
Publication Date | Oct 1, 2008 |
Deposit Date | Oct 9, 2009 |
Journal | Journal of Marketing Theory and Practice |
Print ISSN | 1069-6679 |
Publisher | Taylor and Francis Group |
Peer Reviewed | Peer Reviewed |
Volume | 16 |
Issue | 4 |
Pages | 321-340 |
DOI | https://doi.org/10.2753/mtp1069-6679160405 |
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