On a necessary and sufficient identification condition of optimal treatment regimes with an instrumental variable

Yifan Cui and Eric Tchetgen Tchetgen

Statistics & Probability Letters, 2021, vol. 178, issue C

Abstract: Unmeasured confounding is a threat to causal inference and individualized decision making. Similar to Cui and Tchetgen Tchetgen (2021); Qiu et al. (2021); Han (2021), we consider the problem of identification of optimal individualized treatment regimes with a valid instrumental variable. Han (2021) provided an alternative identifying condition of optimal treatment regimes using the conditional Wald estimand of Cui and Tchetgen Tchetgen (2021); Qiu et al. (2021) 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 (2021); Qiu et al. (2021); Han (2021) and may continue to hold in a variety of potential settings not covered by prior results.

Keywords: Individualized decision making; Policy making; Optimal treatment regimes; Unmeasured confounding; Sign identification; Conditional average treatment effect (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.spl.2021.109180

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