YSPH Biostatistics Seminar- “Learning from shifted data via a semiparametric selection bias modeling”

Note: BIS 526 students are required to attend in person. Others are invited to attend in person but may also attend via zoom.

Speaker- Jiayang Sun, Ph.D.

Title- "Learning from shifted data via a semiparametric selection bias modeling”

Jiayang Sun1, Zixiang Xu1, Mary Meyer2, Jing Qin3

1Department of Statistics, George Mason University

2Colorado State University, 3NIH

Abstract

Data shifts occur in various forms, such as changes in covariates, labels or prior distributions, or domains from the first stage. This talk introduces recent advances in analyzing data with potential selection bias and explores how these relate to broader data-shift frameworks, including co-moving shifts. We present the estimation and testing procedures and demonstrate their effectiveness through theory, simulation studies, and applications to large astronomical and/or heart-transplant datasets, time permitting.

Keywords: Data shifts, selection bias, isotonic inference, smoothing splines, heart transplant, SDSS.