Principles and Applications of Multilevel Modeling in Human Resource Management Research
整合了多层次建模的理论基础与应用方法，针对人力资源管理研究中层级数据的分析需求，讨论了变量概念化、数据聚合、假设检验等关键问题，并通过实证案例演示了跨层次中介调节的实施步骤。
Multilevel modeling is important for human resource management ( HRM ) research in that it often analyzes and interprets hierarchal data residing at more than one level of analysis. However, HRM research in general lags behind other disciplines, such as education, health, marketing, and psychology in the use of a multilevel analytical strategy. This article integrates the most recent literature into the theoretical and applied basics of multilevel modeling applicable to HRM research. A range of multilevel modeling issues have been discussed and they include statistical logic underpinning multilevel modeling, level conceptualization of variables, data aggregation, hypothesis tests, reporting mediation paths, and cross‐level interactions. An empirical example concerning complex cross‐level mediated moderation is presented that will suffice to illustrate the principles and the procedures for implementing a multilevel analytical strategy in HRM research. © 2015 Wiley Periodicals, Inc.