Selecting and Ranking Individualized Treatment Rules With Unmeasured Confounding

Bo Zhang, Jordan Weiss, Dylan S. Small & Qingyuan Zhao
It is common to compare individualized treatment rules based on the value function, which is the expected potential outcome under the treatment rule. Although the value function is not point-identified when there is unmeasured confounding, it still defines a partial order among the treatment rules under Rosenbaum’s sensitivity analysis model. We first consider how to compare two treatment rules with unmeasured confounding in the single-decision setting and then use this pairwise test to rank multiple...
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