Semiparametric regression of the illness-death model with interval censored disease incidence time: An application to the ACLS data. (December 2020)

• Record Type: Journal Article
• Authors: Zhou, Jie; Zhang, Jiajia; McLain, Alexander C; Lu, Wenbin; Sui, Xuemei; Hardin, James W
• Is Part Of: Statistical methods in medical research. Volume 29:Number 12(2020)
• Page Start: 3707
• Page End: 3720
• Publication Date: 2020-12
• Subjects: Semi-competing model -- illlness-death model -- semi-parametric regression -- interval censoring -- Markov models; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280220939123
• Languages: English
• ISSNs: 0962-2802

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.