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

Kwun Chuen Gary Chan, Mei Cheng Wang

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)351-362
Number of pages12
JournalJournal of the American Statistical Association
Volume112
Issue number517
DOIs
StatePublished - Jan 2 2017

Fingerprint

Recurrent Events
Modeling
Regression Model
Directly proportional
Semiparametric Regression Model
HIV Infection
Counting Process
Model
Proportional Hazards Model
Estimating Equation
Failure Time
Clinical Trials
Counting
Estimator
Target
Estimate

Keywords

  • Marked counting process
  • Partial likelihood
  • Recurrent event process
  • Semiparametric models

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

Semiparametric Modeling and Estimation of the Terminal Behavior of Recurrent Marker Processes Before Failure Events. / Chan, Kwun Chuen Gary; Wang, Mei Cheng.

In: Journal of the American Statistical Association, Vol. 112, No. 517, 02.01.2017, p. 351-362.

Research output: Contribution to journalArticle

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