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Activity Number:
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3
- New Developments and Challenges for Dynamic Individualized Treatments
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Type:
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Invited
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Date/Time:
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Sunday, August 7, 2022 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Learning and Data Science
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Abstract #323899
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Title:
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Data adaptive estimation of individualized treatment strategies
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Author(s):
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Ashkan Ertefaie*
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Companies:
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University of Rochester
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Keywords:
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Abstract:
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We propose a method to construct semiparametric or nonparametric decision rules using an inverse probability weighted loss function. We allow the weight functions to be estimated using data-adaptive techniques to reduce the chance of confounding bias. We also propose a conditional value function estimator (i.e., the conditional mean outcome under a treatment regime given a set of variables) and show that the estimator is semiparametrically efficient when the nuisance functions are undersmoothed sufficiently.
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Authors who are presenting talks have a * after their name.
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