PubAg

Main content area

Semiparametric Modeling and Estimation of the Terminal Behavior of Recurrent Marker Processes Before Failure Events

Author:
Chan, Kwun Chuen Gary, Wang, Mei-Cheng
Source:
Journal of the American Statistical Association 2017 v.112 no.517 pp. 351-362
ISSN:
1537-274X
Subject:
HIV infections, clinical trials, equations, models, regression analysis, secondary infection
Abstract:
Recurrent event processes with marker measurements are mostly and largely studied with forward time models starting from an initial event. Interestingly, the processes could exhibit important terminal behavior during a time period before occurrence of the failure event. A natural and direct way to study recurrent events prior to a failure event is to align the processes using the failure event as the time origin and to examine the terminal behavior by a backward time model. This article studies regression models for backward recurrent marker processes by counting time backward from the failure event. A three-level semiparametric regression model is proposed for jointly modeling the time to a failure event, the backward recurrent event process, and the marker observed at the time of each backward recurrent event. The first level is a proportional hazards model for the failure time, the second level is a proportional rate model for the recurrent events occurring before the failure event, and the third level is a proportional mean model for the marker given the occurrence of a recurrent event backward in time. By jointly modeling the three components, estimating equations can be constructed for marked counting processes to estimate the target parameters in the three-level regression models. Large sample properties of the proposed estimators are studied and established. The proposed models and methods are illustrated by a community-based AIDS clinical trial to examine the terminal behavior of frequencies and severities of opportunistic infections among HIV-infected individuals in the last 6 months of life.
Agid:
5683013