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Activity Number:
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457
- Conformal Prediction, Semiparametric Statistics, and Causal Inference
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Type:
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Invited
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Date/Time:
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Wednesday, August 10, 2022 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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Abstract #319268
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Title:
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Inference for Sensitivity Parameters in Causal Inference
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Author(s):
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Larry Wasserman*
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Companies:
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Carnegie Mellon University
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Keywords:
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causal;
confounding
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Abstract:
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Causal inference usually requires the assumption that there is no unmeasured confounding. We consider some approaches to measuring sensitivity to unmeasured confounding in the case of continuous treatments. We consider several types of models: marginal structural models, stochastic intervention models and time varying models.
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Authors who are presenting talks have a * after their name.
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