Online Program Home
My Program

Abstract Details

Activity Number: 285 - Advances in Dimension Reduction and Model Selection for Statistically Challenging Data
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2018 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract #327248 Presentation
Title: Functional Censored Quantile Regression
Author(s): Fei Jiang*
Companies: The University of Hong Kong
Keywords: B-spline; Censored quantile regression; Censored quantile regression; Generalized approximate cross-validation; Time-varying effect

We propose a functional censored quantile regression model to study the relationship between the time to stroke recurrence and the dynamic blood pressure levels, where the time-varying effect is an unspecified function. The B-spline method is used to approximate the coefficient function, which operationally reduces the problem to the parametric estimation. A generalized approximate cross-validation method is devel- oped to select the number of knots by minimizing the expected loss. We demonstrate the asymptotic properties of the estimation and knots selection procedure. Further, we conduct extensive simulation to evaluate the finite sample performance of our method and apply it to analyze the blood pressure and clinical outcome in transient ischemic attack or ischemic stroke data. The results reinforce the importance of the morning surge phenomenon, whose effect has caught attention but remains controversial in the medical literature.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2018 program