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Upcoming Events › Biostats

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January 2021

Division of Biostatistics Seminar with Sam Pimentel

Wednesday, January 27
3:30 pm
- 4:30 pm CST
Virtual United States

Sam Pimentel, of the Department of Statistics at the University of California, Berkeley, will present: "Optimal Tradeoffs in Matched Designs Comparing US-trained and Internationally-trained Surgeons" Abstract: Does receiving a medical education outside the United States impact a surgeon's performance? We study this question by matching operations performed by internationally-trained surgeons to those performed by US-trained surgeons in reanalysis of a large health outcomes study. An effective matched design must achieve several goals, including balancing covariate distributions marginally, ensuring units within…

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February 2021

Division of Biostatistics Seminar with Mary Ryan

Wednesday, February 3
3:30 pm
- 4:30 pm CST
Virtual United States

Mary Ryan, Statistics PhD candidate at the University of California, Irvine, and candidate for a faculty position with the Division of Biostatistics, Coordinating Center for Biometric Research (CCBR), will present: "Sequential Sampling in Prospective Observational Studies" Abstract: Many factors must be taken into account when designing an observational study. Unlike experimental studies, observational studies cannot mitigate the effects of confounding through randomization and such factors should be incorporated into both the study analysis and the study design. Unfortunately, there is…

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Division of Biostatistics PhD Presentation with Adam Kaplan

Friday, February 19
1:00 pm
- 2:00 pm CST
Virtual United States

PhD candidate in Biostatistics, Adam Kaplan, will present: "Context-Driven Prior Distributions in Genome–Wide Association Studies, Medical Device Adaptive Clinical Trials, and Genetic Fine-Mapping" PhD Advisor: Eric Lock Abstract: Present research has gravitated towards making inferences from high-dimensional data, the scenario when we have considerably more variables than the number of observations we have to estimate their effects on a given outcome, and standard statistical methodology cannot be used here. Models assuming that a majority of these variables do not associate…

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