Topic-Contributed Paper Session

Lifetime Data Science (LiDS) Section Student Paper Awards

Tue, Aug 5, 8:30 AM - 10:20 AM Room CC-105B Music City Center

Lifetime Data Science Section co: No Additional Sponsorco: No Additional Sponsor Applied

About this session

In this session, the five student paper award winners from the Lifetime Data Science Section Student Paper Competition will present their award-winning work. These papers collectively cover several exciting novel developments in the field of survival analysis.

5 Presentations

Assessing treatment efficacy for interval-censored endpoints using multistate semi-Markov models fit to multiple data streams

8:35 AM - 8:55 AM

Raphael Morsomme (Food and Drug Administration)

Data Assimilation Interval Censoring Monte Carlo Expectation-Maximization Semi-Markov Multistate Models Panel Data Splines

Design and Analysis of Clinical Trials with Survival Outcome by Incorporating Pre-Randomization Longitudinal Biomarkers

8:55 AM - 9:15 AM

Haolin Li (University of North Carolina at Chapel Hill)

Clinical trial design Longitudinal-survival joint modeling Personalized Treatment Strategies Power Calculation

Doubly Protected Estimation for Survival Outcomes Utilizing External Controls for Randomized Clinical Trials

9:15 AM - 9:35 AM

Chenyin Gao (North Carolina State University)

Adaptive learning Monotone coarsening unmeasured confounding data heterogeneity

Dynamic long-term prediction with intermediate event information: a flexible model with bivariate time-varying coefficients

9:35 AM - 9:55 AM

Yunyi Wang

Co-authors: Wen Li (University of Texas Health Science Center at Houston McGovern Medical School), Ruosha Li (University of Texas School of Public Health), Jing Ning (University of Texas, MD Anderson Cancer Center)

Dynamic prediction, Intermediate event, Landmark time, Long-term prediction, Time-varying effect

Exploring the Heterogeneity in Recurrent Episode Lengths Based On Quantile Regression

9:55 AM - 10:15 AM

Yi Liu

Recurrent episode data Alternating recurrent event process Quantile regression Informative cluster size Dependent truncation