artially nested designs (PNDs) are common in intervention studies in psychology and other social sciences. With this design, participants are assigned to treatment and control groups on an individual basis, but clustering occurs in some but not all groups (e.g., the treatment group). In recent years, there has been substantial development of methods for analyzing data from PNDs. However, little research has been done on causal inference for PNDs, especially for PNDs with nonrandomized treatment assignments. To reduce the research gap, in the current study, we used the expanded potential outcomes framework to define and identify the average causal treatment effects in PNDs. Based on the identification results, we formulated the outcome models that could produce treatment effect estimates with causal interpretation and evaluated how alternative model specifications affect the causal interpretation. We also developed an inverse propensity weighted (IPW) estimation approach and proposed a sandwich-type standard error estimator for the IPW-based estimate. Our simulation studies demonstrated that both the outcome modeling and the IPW methods specified following the identification results can yield satisfactory estimates and inferences of the average causal treatment effects. We applied the proposed approaches to data from a real-life pilot study of the Pregnant Moms' Empowerment Program for illustration. The current study provides guidance and insights on causal inference for PNDs and adds to researchers' toolbox of treatment effect estimation with PNDs. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

中文翻译：

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部分嵌套设计中治疗效果的因果推断。

人工嵌套设计 (PND) 在心理学和其他社会科学的干预研究中很常见。通过这种设计，参与者被单独分配到治疗组和对照组，但聚类发生在一些但不是所有组（例如，治疗组）中。近年来，分析 PND 数据的方法有了长足的发展。然而，关于 PND 的因果推断的研究很少，尤其是对于非随机治疗分配的 PND。为了缩小研究差距，在当前的研究中，我们使用扩展的潜在结果框架来定义和识别 PND 中的平均因果治疗效果。根据鉴定结果，我们制定了可以通过因果解释产生治疗效果估计的结果模型，并评估了替代模型规范如何影响因果解释。我们还开发了一种逆倾向加权 (IPW) 估计方法，并为基于 IPW 的估计提出了一种三明治型标准误差估计量。我们的模拟研究表明，结果建模和识别结果后指定的 IPW 方法都可以对平均因果治疗效果产生令人满意的估计和推论。我们将所提出的方法应用于来自怀孕妈妈赋权计划的现实生活试点研究的数据，以进行说明。当前的研究为 PND 的因果推断提供了指导和见解，并增加了研究人员的 PND 治疗效果估计工具箱。（PsycInfo 数据库记录 (c) 2023 APA，保留所有权利）。