Applying multilevel confirmatory factor analysis techniques to the study of leadership

Abstract

Statistical issues associated with multilevel data are becoming increasingly important to organizational researchers. This paper concentrates on the issue of assessing the factor structure of a construct at aggregate levels of analysis. Specifically, we describe a recently developed procedure for performing multilevel confirmatory factor analysis (MCFA) [Muthen, B.O. (1990). Mean and covariance structure analysis of hierarchical data. Paper presented at the Psychometric Society, Princeton, NJ; Muthen, B.O. (1994). Multilevel covariance structure analysis. Sociological Methods and Research, 22, 376–398], and provide an illustrative example of its application to leadership data reflecting both the organizational and societal level of analysis. Overall, the results of our illustrative analysis support the existence of a valid societal-level leadership construct, and show the potential of this multilevel confirmatory factor analysis procedure for leadership research and the field of I/O psychology in general.