This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
|
403
|
Type:
|
Topic Contributed
|
Date/Time:
|
Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Biometrics Section
|
Abstract - #306810 |
Title:
|
Incorporating Sampling Bias in Analyzing Bivariate Survival Data with Interval Sampling and Application to HIV Research
|
Author(s):
|
Hong Zhu*+ and Mei-Cheng Wang
|
Companies:
|
Johns Hopkins Bloomberg School of Public Health and The Johns Hopkins University
|
Address:
|
Department of Biostatistics, JHSPH, Baltimore, MD, 21205, USA
|
Keywords:
|
Bivariate survival data ;
Copula model ;
Interval sampling ;
Semiparametric estimation ;
Stationarity and semi-stationarity
|
Abstract:
|
In biomedical studies, it is common to collect data with incidence of a disease occurring within a calendar time interval, and bivariate survival data arise and are used as major outcome to identify the progression of a disease. This paper considers an interval sampling scheme, where the first failure event (i.e., HIV infection) is identified within a calender time interval, the occurrence of the initiating event (i.e., birth) can be retrospectively confirmed, and the second failure event (i.e., death) is observed subject to right censoring. The focus is on incorporating sampling bias in analyzing this type of bivariate survival data. In this paper, we develop a copula models method and study the dependency structure of the bivariate survival data. The method is evaluated by simulations and illustrated by Rakai HIV seroconversion data to study the disease progression of HIV infection.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2010 program
|
2010 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.