Principles and applications of multilevel modeling in human resource management research

• Autores: Jie Shen
• Localización: Human Resource Management, ISSN-e 1099-050X, Vol. 55, Nº. 6, 2016, págs. 951-965
• Idioma: inglés
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• Dialnet Métricas: 1 Cita
• Resumen

  • 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. [ABSTRACT FROM AUTHOR]