Gun violence is a major problem in contemporary American society. However, relatively little is known about the effects of firearm injuries on survivors and their family members and how these effects vary across subpopulations. To study these questions and, more generally, to address a gap in the causal inference literature, we present a framework for the study of effect modification or heterogeneous treatment effects in difference-in-differences designs. We implement a new matching technique, which combines profile matching and risk set matching, to (i) preserve the time alignment of covariates, exposure, and outcomes, avoiding pitfalls of other common approaches for difference-in-differences, and (ii) explicitly control biases due to imbalances in observed covariates in subgroups discovered from the data. Our case study shows significant and persistent effects of nonfatal firearm injuries on several health outcomes for those injured and on the mental health of their family members. Sensitivity analyses reveal that these results are moderately robust to unmeasured confounding bias. Finally, while the effects for those injured are modified largely by the severity of the injury and its documented intent, for families, effects are strongest for those whose relative's injury is documented as resulting from an assault, self-harm, or law enforcement intervention.

翻译：枪支暴力是当代美国社会的重大问题。然而，关于枪伤对幸存者及其家庭成员的影响，以及这些影响在不同亚群中的差异，人们所知甚少。为研究这些问题，并更广泛地弥合因果推断文献中的空白，我们提出一个在双重差分设计中研究效应修饰或异质性处理效应的框架。我们实现了一种结合轮廓匹配和风险集匹配的新匹配技术，旨在：(i) 保持协变量、暴露与结局的时间对齐，避免其他常见双重差分方法的陷阱；(ii) 明确控制从数据中发现的亚组内观测协变量失衡导致的偏倚。案例研究表明，非致命枪伤对伤者的多项健康结局及其家庭成员的心理健康具有显著且持续的影响。敏感性分析显示，这些结果对未观测混杂偏倚具有中等稳健性。最后，尽管伤者的影响主要由损伤严重程度及其记录意图所修饰，但对家庭而言，当其亲属的损伤记录源于袭击、自伤或执法干预时，影响最为强烈。