JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 193
Type: Contributed
Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #315010
Title: Sieve Estimation for Partial Linear Models with Applications to Cox-Type Models
Author(s): Jiajun Xu* and Kwok Fai Lam
Companies: The University of Hong Kong and The University of Hong Kong
Keywords: asymptotically efficient ; glioblastoma multiforme ; nonlinear age effect ; partial linear Cox model ; sieve maximum partial likelihood
Abstract:

Interest in semiparametric modeling of the covariate effects is growing with wide applications in medical research. This paper studies the importance of adjusting the potential nonlinear age effect appropriately for the valid statistical inference on the treatment effect, and suggests a simple estimation method based on the sieve maximum likelihood estimation method for the general partial linear models with illustrations using the partial linear semiparametric Cox types models. The proposed method is particularly simple and can be implemented directly using standard statistical softwares. A data-driven method to determine the optimal locations and the number of knots is also considered that this algorithm is able to identify the changing point where the effect of the covariates is very different before and after the changing point or threshold value. Simulation studies are carried out to study the performance of the proposed method. For illustration purpose, the method is applied to a glioblastoma multiforme data set with the age at diagnosis of the patients ranges from 5 to 92 years old.


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

Back to the full JSM 2015 program





For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

2015 JSM Online Program Home