Expanding the methodological toolbox of HRM researchers: The added value of latent bathtub models and optimal matching analysis
提出潜浴缸模型和最优匹配分析两种方法，帮助人力资源管理研究者处理层级和纵向数据，并以员工敬业度研究为例展示其应用价值。
Researchers frequently rely on general linear models (GLMs) to investigate the impact of human resource management (HRM) decisions. However, the structure of organizations and recent technological advancements in the measurement of HRM processes cause contemporary HR data to be hierarchical and/or longitudinal. At the same time, the growing interest in effects at different levels of analysis and over prolonged periods of time further drives the need for HRM researchers to differentiate from traditional methodology. While multilevel techniques have become more common, this article proposes two additional methods that may complement the current methodological toolbox of HRM researchers. Latent bathtub models can accurately describe the multilevel mechanisms occurring in organizations, even if the outcome resides at the higher level of analysis. Optimal matching analysis can be useful to unveil longitudinal patterns in HR data, particularly in contexts where HRM processes are measured on a continuous basis. Illustrating the methods’ applicability to research on employee engagement, this paper demonstrates that the HRM community—both research and practice—can benefit from a more diversified methodological toolbox, drawing on techniques from within and outside the direct field to improve the decision‐making process.