论文标题
在具有仪器变量的最佳治疗方案的必要且充分的识别条件下
On a necessary and sufficient identification condition of optimal treatment regimes with an instrumental variable
论文作者
论文摘要
无法衡量的混杂是对因果推论和个性化决策的威胁。类似于CUI和TCHETGEN TCHETGEN（2020）； Qiu等。 （2020）;汉（2020a），我们考虑了具有有效仪器变量的最佳个性化治疗方案的鉴定问题。 Han（2020a）使用有条件的CUI和TCHETGEN TCHETGEN（2020）提供了最佳治疗方案的替代识别条件； Qiu等。 （2020）当治疗分配受到内生性和有效的二元仪器变量时。在本说明中，我们提供了使用条件WALD估计的最佳治疗方案的必要条件。 CUI和TCHETGEN TCHETGEN（2020）必须暗示我们的新型状况。 Qiu等。 （2020）; Han（2020a），可能会继续持有各种未涵盖的潜在环境。
Unmeasured confounding is a threat to causal inference and individualized decision making. Similar to Cui and Tchetgen Tchetgen (2020); Qiu et al. (2020); Han (2020a), we consider the problem of identification of optimal individualized treatment regimes with a valid instrumental variable. Han (2020a) provided an alternative identifying condition of optimal treatment regimes using the conditional Wald estimand of Cui and Tchetgen Tchetgen (2020); Qiu et al. (2020) when treatment assignment is subject to endogeneity and a valid binary instrumental variable is available. In this note, we provide a necessary and sufficient condition for identification of optimal treatment regimes using the conditional Wald estimand. Our novel condition is necessarily implied by those of Cui and Tchetgen Tchetgen (2020); Qiu et al. (2020); Han (2020a) and may continue to hold in a variety of potential settings not covered by prior results.
