Difference-in-difference (DID) estimators are a valuable method for identifying causal effects in the public health researcher's toolkit. A growing methods literature points out potential problems with DID estimators when treatment is staggered in adoption and varies with time. Despite this, no practical guide exists for addressing these new critiques in public health research. We illustrate these new DID concepts with step-by-step examples, code, and a checklist. We draw insights by comparing the simple 2 × 2 DID design (single treatment group, single control group, two time periods) with more complex cases: additional treated groups, additional time periods of treatment, and treatment effects possibly varying over time. We outline newly uncovered threats to causal interpretation of DID estimates and the solutions the literature has proposed, relying on a decomposition that shows how the more complex DID are an average of simpler 2 × 2 DID subexperiments.Expected final online publication date for the Annual Review of Public Health, Volume 45 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

中文翻译：

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设计采用交错治疗的双重差异研究：关键概念和实践指南

双重差分 (DID) 估计量是公共卫生研究人员工具包中识别因果效应的一种有价值的方法。越来越多的方法文献指出，当治疗采用交错方式且随时间变化时，DID 估计器存在潜在问题。尽管如此，仍然没有实用指南来解决公共卫生研究中的这些新批评。我们通过分步示例、代码和清单来说明这些新的 DID 概念。我们通过比较简单的 2 × 2 DID 设计（单一治疗组、单一对照组、两个时间段）与更复杂的案例（额外的治疗组、额外的治疗时间段以及可能随时间变化的治疗效果）得出见解。我们概述了新发现的对 DID 估计因果解释的威胁以及文献提出的解决方案，依赖于分解，显示更复杂的 DID 如何平均为更简单的 2 × 2 DID 子实验。年度回顾的预计最终在线发布日期of Public Health，第 45 卷为 2024 年 4 月。请参阅 http://www.annualreviews.org/page/journal/pubdates 了解修订后的估计。