Efficient Estimation of Optimal Regimes Under a No Direct Effect Assumption

Lin Liu, Zach Shahn, James M. Robins & Andrea Rotnitzky
We derive new estimators of an optimal joint testing and treatment regime under the no direct effect (NDE) assumption that a given laboratory, diagnostic, or screening test has no effect on a patient’s clinical outcomes except through the effect of the test results on the choice of treatment. We model the optimal joint strategy with an optimal structural nested mean model (opt-SNMM). The proposed estimators are more efficient than previous estimators of the parameters of...
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