This paper reviews and details methods for state policy evaluation to guide selection of a research approach based on evaluation setting and available data. We highlight key design considerations for an analysis, including treatment and control group selection, timing of policy adoption, expected effect heterogeneity, and data considerations. We then provide an overview of analytic approaches and differentiate between methods based on evaluation context, such as settings with no control units, a single treated unit, multiple treated units, or with multiple treatment cohorts. Methods discussed include interrupted time series models, difference-in-differences estimators, autoregressive models, and synthetic control methods, along with method extensions which address issues like staggered policy adoption and heterogenous treatment effects. We end with an illustrative example, applying the developed framework to evaluate the impacts of state-level naloxone standing order policies on overdose rates. Overall, we provide researchers with an approach for deciding on methods for state policy evaluations, which can be used to select study designs and inform methodological choices.

翻译：本文综述并详述了州政策评估的方法，旨在基于评估情境和可用数据指导研究路径的选择。我们重点分析了评估中的关键设计考量，包括处理组与对照组的选择、政策采纳时机、预期效应异质性以及数据考量。随后，我们概述了分析方法体系，并根据评估情境（如无对照组单元、单一处理单元、多处理单元或多处理队列等场景）对方法进行了区分。讨论的方法包括间断时间序列模型、双重差分估计量、自回归模型以及合成控制方法，同时涵盖了处理交错政策采纳和异质性处理效应等问题的扩展方法。最后，我们通过一个示例性案例，应用所构建的框架评估了州级纳洛酮常备医嘱政策对药物过量率的影响。总体而言，我们为研究者提供了一套用于确定州政策评估方法的决策框架，该框架可用于选择研究设计并指导方法学决策。