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208
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Tue, 8/10/2021,
1:30 PM -
3:20 PM
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Virtual
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Personalized and Precision Medicine — Contributed Speed
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Biometrics Section
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Chair(s): Madan G Kundu, Daiichi Sankyo, Inc.
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1:35 PM
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Optimal Personalized Treatment Selection with Multivariate Outcome Measures in a Multiple Treatment Case
Chathura Siriwardhana, University of Hawaii; KB Kulasekara, University of Louisville
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1:40 PM
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Synergistic Self-Learning Approach to Establishing Personal Nutrition Intervention Schemes from Multiple Benefit Outcomes in a Calcium Supplementation Trial
Yiwang Zhou, Department of Biostatistics, University of Michigan; Peter X.K. Song, University of Michigan
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1:45 PM
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Investigating Stability in Subgroup Identification for Stratified Medicine
Gleicy Macedo Hair, Merck & Co., Inc.; Thomas Jemielita, Merck & Co., Inc.; Shahrul Mt-Isa , MSD; Patrick Schnell, The Ohio State University College of Public Health; Richard Baumgartner, Merck Research Laboratories
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1:50 PM
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A Nonparametric Bayesian Approach for Adjusting Partial Compliance in Sequential Decision-Making
Indrabati Bhattacharya, University of Rochester; Ashkan Ertefaie, University of Rochester; Andrew Gordon Wilson, New York University; Brent Johnson, University of Rochester; James Mckay, University of Pennsylvania; Kevin Lynch, University of Pennsylvania
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1:55 PM
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Comparison of Methods for Estimating Optimal Dynamic Treatment Regimes
Yingyi Liu, AbbVie; Hongwei Wang, AbbVie; Weili He, AbbVie
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2:00 PM
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Estimating Optimal Treatment Decision Rules When Data Are Missing
Jenny Shen, University of Pennsylvania; Kristin Linn, University of Pennsylvania
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2:05 PM
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Statistics Methods for Assessing Drug Interactions Using Observational Data
Qian Xu, University of Louisville; Maiying Kong, University of Louisville
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2:10 PM
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Constructing Dynamic Treatment Regimes in Presence of Noncompliance
Ashkan Ertefaie, University of Rochester; Cuong Pham, University of Rochester, Dept of Biostatistics and Computational Biology
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2:15 PM
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Relative Contrast Estimation and Inference for Treatment Recommendation
Muxuan Liang, Fred Hutchinson Cancer Research Center; Menggang Yu, University of Wisconsin
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2:20 PM
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Design Considerations and Analytical Framework for Reliably Identifying a Beneficial Individualized Treatment Rule
Charles H Cain, University of Minnesota; Thomas Murray, Division of Biostatistics, University of Minnesota; Kyle D Rudser, University of Minnesota; Alexander J Rothman, University of Minnesota; Anne C Melzer, Minneapolis VA Health Care System; Anne M Joseph, University of Minnesota
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2:30 PM
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Developing prediction models when there are systematically missing predictors in an individual patient data meta-analysis
Michael Seo, University of Bern
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2:35 PM
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Transportability of Causal Inference Under Probabilistic Dynamic Treatment Regimes for Organ Transplantation
Grace R Lyden, University of Minnesota School of Public Health; David M Vock, University of Minnesota School of Public Health
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2:40 PM
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Adaptive Combination of Conditional Average Treatment Effects Based on Randomized and Observational Data
David Cheng, Massachusetts General Hospital; Tianxi Cai, Harvard T.H. Chan School of Public Health
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2:45 PM
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Counterfactual Prediction to Support Individualized Decisions on Treatment Initiation
Pawel Morzywolek, Ghent University; Stijn Vansteelandt, Ghent University
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2:50 PM
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Weighting for Generalization and Personalization of Causal Inferences
Ambarish Chattopadhyay, Harvard University; Eric Cohn, Harvard University; Jose Zubizarreta, Harvard University
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2:55 PM
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Modeling of Q-Functions in Q-Learning
Xiaoxi Yan, Duke–NUS Medical School; Zhiguo Li, Duke University
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3:00 PM
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MoTR and PSTn: Building a Causal Engine for Estimating the Within-Individual Average Treatment Effect Using Wearable Sensors
Eric J. Daza, Evidation Health; Logan Schneider, Stanford Medicine, Alphabet
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3:05 PM
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Predicting Current and Future Individual Benefits of Medical Treatments Using 2-Dimensional Personalized Medicine Models
Francisco Diaz, The University of Kansas Medical Center
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3:10 PM
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Variable Selection for Interval-Censored Data with Time-Varying Coefficients and Application to Alzheimer's Disease
Kaiyi Chen, University of Missouri-Columbia; Jianguo Sun, Univerisity of Missouri-Columbia
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3:15 PM
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Semiparametric Maximum Likelihood Estimation of Panel Count Data with Time-Dependent Covariates and Time-Varying Coefficients
Yuanyuan Guo, University of Missouri, Columbia
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