Recent Methodological Developments and Applications in Statistical and Machine Learning Approaches for Predictive Modeling Using Competing Risk Data — Topic-Contributed Papers
Section on Risk Analysis, Section on Statistical Consulting, Section on Statistics in Epidemiology
Organizer(s): Nilotpal Sanyal, Stanford University School of Medicine
Chair(s): Maya Mathur, Stanford University
10:05 AM
Scalable Algorithms for Large-Scale Competing Risks Data Eric Kawaguchi, University of Southern California; Jenny Shen, University of California Los Angeles; Gang Li, University of California Los Angeles; Marc Suchard, University of California Los Angeles
Assessing the Predictive Performance of Biomarkers in the Presence of Competing Risks Due to Transplantation
Cuihong Zhang, The University of Texas Health Science Center at Houston; Jing Ning, The University of Texas MD Anderson Cancer Center; Steven Belle, University of Pittsburgh; Robert Squires, University of Pittsburgh; Jianwen Cai, The University of North Carolina at Chapel Hill; Ruosha Li, The University of Texas Health Science Center at Houston
Risk analysis and related topics — Contributed Speed
Section on Risk Analysis
Chair(s): Indranil Ghosh, University of North Carolina Wilmington
10:05 AM
Extending the Concordance Index to Left-Truncated Time-to-Event Data Nicholas Hartman, Department of Biostatistics, University of Michigan-Ann Arbor; Sehee Kim, Department of Clinical Epidemiology and Biostatistics, Asan Medical Center; Kevin He, University of Michigan; John D. Kalbfleisch, University of Michigan
Dynamic Risk Prediction for Cervical Precancer Screening with Continuous and Binary Longitudinal Biomarkers Siddharth Roy, National Cancer Institute and University of Maryland Baltimore County; Anindya Roy, U.S. Census Bureau/ UMBC; Megan A. Clarke, National Cancer Institute; Ana Gradissimo, Albert Einstein College of Medicine; Robert D. Burk, Albert Einstein College of Medicine; Nicolas Wentzensen, National Cancer Institute; Paul S. Albert, National Cancer Institute; Danping Liu, National Cancer Institute/National Institutes of Health
The 2020 U.S. Stock Market Crash Min Shu, University of Wisconsin Stout; Ruiqiang Song, Michigan Technological University; Wei Zhu, Stony Brook University
