Affordable Access

deepdyve-link
Publisher Website

A varying-coefficient generalized odds rate model with time-varying exposure: An application to fitness and cardiovascular disease mortality.

Authors
  • Zhou, Jie1
  • Zhang, Jiajia1
  • Mclain, Alexander C1
  • Lu, Wenbin2
  • Sui, Xuemei3
  • Hardin, James W1
  • 1 Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, South Carolina.
  • 2 Department of Statistics, North Carolina State University, Raliegh, North Carolina.
  • 3 Department of Exercise, University of South Carolina, Columbia, South Carolina.
Type
Published Article
Journal
Biometrics
Publisher
Wiley (Blackwell Publishing)
Publication Date
Sep 01, 2019
Volume
75
Issue
3
Pages
853–863
Identifiers
DOI: 10.1111/biom.13057
PMID: 31132151
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Varying-coefficient models have become a common tool to determine whether and how the association between an exposure and an outcome changes over a continuous measure. These models are complicated when the exposure itself is time-varying and subjected to measurement error. For example, it is well known that longitudinal physical fitness has an impact on cardiovascular disease (CVD) mortality. It is not known, however, how the effect of longitudinal physical fitness on CVD mortality varies with age. In this paper, we propose a varying-coefficient generalized odds rate model that allows flexible estimation of age-modified effects of longitudinal physical fitness on CVD mortality. In our model, the longitudinal physical fitness is measured with error and modeled using a mixed-effects model, and its associated age-varying coefficient function is represented by cubic B-splines. An expectation-maximization algorithm is developed to estimate the parameters in the joint models of longitudinal physical fitness and CVD mortality. A modified pseudoadaptive Gaussian-Hermite quadrature method is adopted to compute the integrals with respect to random effects involved in the E-step. The performance of the proposed method is evaluated through extensive simulation studies and is further illustrated with an application to cohort data from the Aerobic Center Longitudinal Study. © 2019 International Biometric Society.

Report this publication

Statistics

Seen <100 times