Using hierarchical linear modeling to investigate the moderating influence of leadership climate

When confronted with multilevel data, e.g., when individuals are nested within work groups, hierarchical linear modeling (HLM) [Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models. Newbury Park, CA: SAGE Publications.] can provide a powerful analytical approach. Using the common...

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Bibliographic Details
Published in:The Leadership quarterly 2002-02, Vol.13 (1), p.15-33
Main Authors: Gavin, Mark B., Hofmann, David A.
Format: Article
Language:English
Subjects:
Hierarchies
Leadership
Linear programming
Studies
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Summary:When confronted with multilevel data, e.g., when individuals are nested within work groups, hierarchical linear modeling (HLM) [Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models. Newbury Park, CA: SAGE Publications.] can provide a powerful analytical approach. Using the common data set and the theoretical framework presented in the introductory paper as a foundation, we begin by providing a brief introduction to the HLM analytical framework and describe the basic HLM model. Next, we develop a set of hypotheses concerning relationships among task significance, leadership climate, and hostility both within and across levels of analysis. We then describe and test a series of HLM models designed to investigate these hypotheses. Finally, we conclude with a brief discussion of the interpretation and implications of the results as well as the benefits of HLM in the context of multilevel modeling.
ISSN:1048-9843
1873-3409
DOI:10.1016/S1048-9843(01)00102-3