The American Statistical Association (ASA) Section on Lifetime Data Analysis (LiDS) is pleased to announce our next webinar!
Title: Statistical analysis with the occurrence of a terminal event
Speaker: Bin Nan, Ph.D., Chancellor's Professor, Department of Statistics, UC Irvine
Date and Time: November 14, 2025, 12:00 – 2:00 PM ET
Location: Via Zoom, register here, https://amstat.users.membersuite.com/events/2e04bc98-0078-c11e-57e6-0b48ca99df83/details
Sponsor: Lifetime Data Science Section
Registration Deadline: TBA
Abstract: In cohort studies, time plays important roles in data collection and data analysis. Two distinct sets of statistical tools have been developed primarily for analyzing data in cohort studies: one is longitudinal data analysis that focuses on properly handling temporal dependence among repeatedly collected measurements over time, one is survival analysis that deals with time-to-event data when censoring occurs. In this webinar, I will present some recently developed more interpretable work on analyzing data in cohort studies in a particular situation: a terminal event occurs.
For analyzing longitudinal data with the occurrence of a terminal event that is subject to right censoring, I will first introduce the idea of conditional modeling given the terminal event time (usually death time) via a parametric model, then extend it to a more robust nonparametric bivariate time-varying coefficient model in which the time-varying coefficients capture the longitudinal trajectories of covariate effects along with both the follow-up time and the residual lifetime.
For analyzing time-to-event data, e.g. disease onset, with the occurrence of a terminal event, in contrast to the commonly used semi-competing risks or illness-death model, I will introduce a nonparametric estimation of the distribution of the disease onset time conditional on the death time, which consists of two components that provide straightforward interpretations of the disease onset during the lifespan. Regression models are constructed for these two components when evaluating risk factors of disease onset is of interest.
All these statistical developments are motivated by real studies. In addition to presenting statistical properties and simulation results, I will also present the results of several data examples analyzed by the proposed methods.
Registration link: https://amstat.users.membersuite.com/events/2e04bc98-0078-c11e-57e6-0b48ca99df83/details
Registration Fees:
Lifetime Data Science Section Members: $20
ASA Members: $30
Student ASA Member: $25
Nonmembers: $45
Access Information
After registering, you will receive a confirmation email. In the body of the confirmation email, you will receive the Zoom link for the webinar.
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Zhe Fei
Assistant Professor
University of California, Riverside
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