JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 177
Type: Contributed
Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract #314961
Title: Semiparametric Random-Effect Models for Panel Count Data with Informative Observation Times
Author(s): Yang Li* and Yanqing Sun
Companies: The University of North Carolina at Charlotte and The University of North Carolina at Charlotte
Keywords: Estimating equation ; Informative censoring ; Informative observation process ; Panel count data ; Semiparametric regression
Abstract:

Panel count data frequently arise from many fields such as medical follow-up studies concerning certain recurrent events. In such situations, the responses are recorded only at discrete observation times. Most existing approaches on panel count data analysis assumed that the observation or follow-up times are independent of the recurrent event process either completely or given some covariates. We present a joint analysis approach in which the possible correlations among the responses, observation and follow-up times can be characterized by time-dependent random effects. Estimating equations are developed for the parameter estimation and the resulted estimates are shown to be consistent and asymptotically normal. A simulation study is conducted to assess the finite sample performance of the approach and the method is applied to data arising from a skin cancer study.


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