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

Abstract

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.