Semiparametric regression of the illness-death model with interval censored disease incidence time: An application to the ACLS data

Author:

Zhou Jie1,Zhang Jiajia1ORCID,McLain Alexander C1,Lu Wenbin2,Sui Xuemei3,Hardin James W1

Affiliation:

1. Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA

2. Department of Statistics, North Carolina State University, Raleigh, NC, USA

3. Exercise Science, University of South Carolina, Columbia, SC, USA

Abstract

To investigate the effect of fitness on cardiovascular disease and all-cause mortality using the Aerobics Center Longitudinal Study, we develop a semiparametric illness-death model account for intermittent observations of the cardiovascular disease incidence time and the right censored data of all-cause mortality. The main challenge in estimation is to handle the intermittent observations (interval censoring) of cardiovascular disease incidence time and we develop a semiparametric estimation method based on the expectation-maximization algorithm for a Markov illness-death regression model. The variance of the parameters is estimated using profile likelihood methods. The proposed method is evaluated using extensive simulation studies and illustrated with an application to the Aerobics Center Longitudinal Study data.

Publisher

SAGE Publications

Subject

Health Information Management,Statistics and Probability,Epidemiology

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