Determining which organizations are more effective in implementing an intervention program is essential for theoretically and empirically characterizing exemplary practice and for intervening to enhance the capacity of ineffective ones. Yet sites differ in their local ecological conditions including client composition, alternative programs, and community context. Applying the causal inference framework, this study proposes a formal mathematical definition for the local relative effectiveness of an organization attributable solely to malleable organizational practice. Capitalizing on multisite randomized trials, the identification leverages observed control group outcomes that capture some of the confounding impacts of otherwise unmeasured contextual variation. We propose a two-step mixed-effects modeling (2SME) procedure that adjusts for pre-existing between-site variation. A series of Monte Carlo simulations reveals its superior performance in comparison with conventional methods. We apply the new strategy to an evaluation of Job Corps centers nationwide serving disadvantaged youths.

翻译：确定哪些组织在实施干预计划方面更为有效，对于从理论和实证层面界定典范实践，以及介入提升低效组织能力至关重要。然而，各站点在本地生态条件上存在差异，包括服务对象构成、替代性方案及社区背景等。本研究基于因果推断框架，提出了一个关于组织本地相对效能的正式数学定义，该效能仅归因于可调整的组织实践。通过利用多站点随机试验，识别过程借助观察到的对照组结果来捕捉部分由未测量情境变异导致的混杂影响。我们提出了一种两步混合效应建模（2SME）程序，以调整站点间预先存在的变异。一系列蒙特卡洛模拟显示，相较于传统方法，该程序具有更优性能。我们将这一新策略应用于全国范围内服务弱势青年的职业培训中心的评估中。