Cancer Biostatistics Faculty Candidate Seminar - Hongyuan Cao, PhD, Stony Brook University
Kernel meets sieve: transformed hazards models with sparse longitudinal covariates
Event Details
Date
Friday, February 28, 2025
Time
1-2 p.m.
Location
Description
Dr. Cao proposes combining kernel-weighted log-likelihood and sieve maximum log-likelihood estimation to conduct statistical inference in a robust and easy to implement method. The establish the asymptotic properties of the proposed estimator and contribute to a rigorous theoretical framework for general kernel-weighted sieve M-estimators. The analysis of a data set from a COVID-19 study in Wuhan identifies clinical predictors that cannot be obtained using existing methods.
Cost
Free
Contact
Accessibility
We value inclusion and access for all participants and are pleased to provide reasonable accommodations for this event. Please email nachreiner3@wisc.edu to make a disability-related accommodation request. Reasonable effort will be made to support your request.