When treatment cannot be manipulated, propensity score analysis provides a useful way to making causal claims under the assumption of no unobserved confounders. However, it is still rarely utilised in leadership and applied psychology research. The purpose of this paper is threefold. First, it explains and discusses the application and key assumptions of the method with a particular focus on propensity score weighting. This approach is readily implementable since a weighted regression is available in most statistical software. Moreover, the approach can offer a “double robust” protection against misspecification of either the propensity score or the outcome model by including confounding variables in both models. A second aim is to discuss how propensity score analysis (and propensity score weighting, specifically) has been conducted in recent management studies and examine future challenges. Finally, we present an advanced application of the approach to illustrate how it can be employed to estimate the causal impact of leadership succession on performance using data from Italian football. The case also exemplifies how to extend the standard single treatment analysis to estimate the separate impact of different managerial characteristic changes between the old and the new manager.

当无法操纵治疗时，倾向得分分析提供了一种有用的方法，可以在没有未观察到的混杂因素的假设下做出因果声明。然而，它仍然很少用于领导力和应用心理学研究。本文的目的有三个。首先，它解释和讨论了该方法的应用和关键假设，特别关注倾向得分加权。这种方法很容易实施，因为大多数统计软件都提供加权回归。此外，该方法可以通过在两个模型中包含混杂变量来提供“双重稳健”保护，防止倾向得分或结果模型的错误指定。第二个目标是讨论倾向得分分析（和倾向得分加权，特别是）在最近的管理研究中进行了研究，并研究了未来的挑战。最后，我们展示了该方法的高级应用，以说明如何使用意大利足球的数据来估计领导层继任对绩效的因果影响。该案例还举例说明了如何扩展标准的单一处理分析，以估计新旧经理之间不同管理特征变化的单独影响。