Applying multilevel confirmatory factor analysis techniques to the study of leadership
Applying multilevel confirmatory factor analysis techniques to the study of leadership
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DOI：
10.1016/j.leaqua.2004.09.009
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发表时间：
2005-02-01
影响因子：
7.5
通讯作者：
Hall, RJ
中科院分区：
文献类型：
--
作者：
Dyer, NG;Hanges, PJ;Hall, RJ
与多层次数据相关的统计问题对组织研究者来说变得越来越重要。本文集中于在总体分析水平上评估一个结构的因素结构的问题。具体来说，我们描述了一个最近开发的程序进行多层次验证性因素分析（MCFA）[穆森，B.O.（1990年）。分层资料的均值和协方差结构分析。论文发表于心理测量学会，普林斯顿，新泽西州; Muten，B.O.（1994年）。多水平协方差结构分析。社会学方法和研究，22，376-398]，并提供了一个说明性的例子，其应用到领导数据反映了组织和社会层面的分析。总体而言，我们的说明性分析的结果支持存在一个有效的社会层面的领导结构，并显示了这种多层次的验证性因素分析程序的领导研究和I/O心理学领域的潜力。(c)2004年爱思唯尔公司All rights reserved.
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. (c) 2004 Elsevier Inc. All rights reserved.