Covariate Adjustment in Randomized Clinical Trials: New Methods and Applications
While baseline characteristics tend to be balanced in a randomized clinical trial, adjusting for prognostic covariates can improve the statistical power to detect treatment effects. Although this principle is well known, questions about how to effectively and validly implement covariate adjustment are an area of active biostatistical research. Our speakers will cover topics of broad relevance to the field, as well as more specific work related to covariate adjustment in group-sequential and re-randomization designs, complexities of adjustment in the face of missing covariate data, machine-learning for covariate selection and the role of covariate adjustment in the drug and device approval process. The conference includes morning and afternoon panels discussions along with time for audience participation. We offer in-person and virtual options. In-person registration includes breakfast and lunch with multiple opportunities for networking.
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For more information click here: cvent.me/obNnA9 |
We hope you'll join us for this wonderful conference!
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Mary Putt, ScD
Program Committee Chair
Department of Biostatistics, Epidemiology & Informatics
Perelman School of Medicine, University of Pennsylvania
University of Pennsylvania
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