JSM2023
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Topic-Contributed Paper Session

Trees and Random Forests for Analyzing Complex Data

Mon, Aug 7, 8:30 AM
Jeffrey SimonoffOrganizerDenis LarocqueOrganizerWenbo JingChair
Section on Statistical Learning and Data Science

5 Presentations

A Regression Tree Method for Longitudinal and Clustered Data with Multivariate Responses
8:35 AM - 8:55 AM
Jeffrey Simonoff (New York University)
Co-authors: Wenbo Jing
Regression Trees and Random Forests for Interval Censored Data
8:55 AM - 9:15 AM
Liqun Diao
Co-authors: Ce Yang (Vertex Pharmaceuticals), Xianwei Li (University of Waterloo), Richard Cook (University of Waterloo)
Covariance Regression with Random Forests
9:15 AM - 9:35 AM
Denis Larocque (HEC Montreal)
Co-authors: Cansu Alakus (HEC Montréal), Labbe Aurélie (HEC Montréal)
Random forest missing data imputation for clustered and longitudinal data
9:35 AM - 9:55 AM
Jaime Speiser (Wake Forest School of Medicine)
Random forests for individualized treatment regimes for multiple treatments, applied to observational student success studies
9:55 AM - 10:15 AM
Juanjuan Fan (San Diego State University)
Co-authors: Justin Thorpe, Richard Levine (San Diego State University), Luo Li
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