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Activity Number: 277 - SPEED: Biometrics and Environmental Statistics Part 1
Type: Contributed
Date/Time: Tuesday, August 9, 2022 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #322667
Title: A Multiple Imputation Approach for Optimal Treatment Decision Rules
Author(s): Jenny Shen* and Kristin Linn
Companies: University of Pennsylvania and University of Pennsylvania
Keywords: individualized treatment regime; decision rule; multiply imputed data

Individual patients, care providers, and other stakeholders can benefit from the development and implementation of data-driven optimal treatment strategies. Optimal treatment regimes can improve outcomes and lower healthcare costs through optimal treatment decision rules, which maximize a population-level distributional summary such as the expected value of a clinical outcome. Guidance for estimating optimal decision rules in the presence of missing data is fairly limited, as the majority of existing methods rely on having a complete set of data that are observed. The Social incentives to Encourage Physical Activity and Understand Predictors (STEP UP) trial was a randomized trial comparing multiple interventions that aimed to increase daily step counts among employees at a large professional services company. Using simulations, we propose a multiple imputation framework for estimating optimal decision rules for data with missingness, discuss guidance for reproducible inference, and apply our findings to data from the STEP UP trial.

Authors who are presenting talks have a * after their name.

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