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Frontiers in Biostatistics: Statistical Modeling and Adjustment for Sampling Biases
January 12 @ 1:00 pm - 2:00 pm
Jing Ning, PhD
Associate Professor. Department of Biostatistics
Division of Quantitative Sciences
The University of Texas M.D. Anderson Cancer Center
Register at: https://bit.ly/FIBJan12
Abstract: Bias sampling mechanisms are commonly encountered in applications where the subjects in a target population are not given an equal chance to be selected, either accidentally, by natural circumstances, or intentionally by design. Statistical methods not properly accounting for such a challenge often lead to invalid inferences. For example, evidence combined from published studies may lead to overly optimistic conclusions due to publication bias, and the well-known length bias can cause the screening to appear to be more successful than it really is. In this talk, I will present our recent work to adjust the sampling biases in diverse applications such as the survivorship bias in prevalent cohort, the self-reporting bias in longitudinal analysis and the publication bias in meta-analysis.