Estimating Equation-Based Approaches for Complex Longitudinal Data: High-Dimensional Inference and Transfer Learning
Lu Xia, PhD
Assistant Professor
Department of Statistics and Probability |
Michigan State University
WHEN: Wednesday, Sept 4, 2024, from 3:30 to 4:30 p.m.
WHERE: Virtual |
NOTE: Lu Xia will be presenting from Michigan
Abstract
Regression analysis of longitudinal data, where correlated responses from multiple time points are measured, is ubiquitous in many scientific areas such as biology, medicine and sociology. New challenges are emerging with the availability of complex longitudinal data in this big data era. Generalized estimating equations (GEE) are widely used to analyze longitudinal data, which can achieve consistency and improve efficiency. The first part of this talk will introduce a projected estimating equation approach to reliably drawing inference for linear functionals of regression parameters in GEE in high-dimensional settings, where the number of covariates (such as proteomic features) may exceed the sample size. The second part of this talk will focus on a transfer learning approach for GEE that facilitates parameter estimation and prediction in the target population when external models from larger cohorts are readily available.
Speaker Bio
Lu Xia is an Assistant Professor in the Department of Statistics and Probability at Michigan State University. Before joining Michigan State in 2023, she earned her PhD in Biostatistics from the University of Michigan and worked as a Postdoctoral Scholar in the Department of Biostatistics at the University of Washington after graduation. Her current research focuses on high-dimensional statistics, data integration, machine learning and multi-omics data analysis. For more information, please visit .
听
听