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https://doi.org/10.1016/j.spl.2021.109180
DC Field | Value | |
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dc.title | On a necessary and sufficient identification condition of optimal treatment regimes with an instrumental variable | |
dc.contributor.author | Cui, Yifan | |
dc.contributor.author | Tchetgen Tchetgen, E. | |
dc.date.accessioned | 2022-10-13T01:17:46Z | |
dc.date.available | 2022-10-13T01:17:46Z | |
dc.date.issued | 2021-11-01 | |
dc.identifier.citation | Cui, Yifan, Tchetgen Tchetgen, E. (2021-11-01). On a necessary and sufficient identification condition of optimal treatment regimes with an instrumental variable. Statistics and Probability Letters 178 : 109180. ScholarBank@NUS Repository. https://doi.org/10.1016/j.spl.2021.109180 | |
dc.identifier.issn | 0167-7152 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/232898 | |
dc.description.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. © 2021 | |
dc.publisher | Elsevier B.V. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.source | Scopus OA2021 | |
dc.subject | Conditional average treatment effect | |
dc.subject | Individualized decision making | |
dc.subject | Optimal treatment regimes | |
dc.subject | Policy making | |
dc.subject | Sign identification | |
dc.subject | Unmeasured confounding | |
dc.type | Article | |
dc.contributor.department | STATISTICS AND DATA SCIENCE | |
dc.description.doi | 10.1016/j.spl.2021.109180 | |
dc.description.sourcetitle | Statistics and Probability Letters | |
dc.description.volume | 178 | |
dc.description.page | 109180 | |
Appears in Collections: | Elements Staff Publications |
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