TY - JOUR
T1 - Marginal additive hazards model for case-cohort studies with multiple disease outcomes
T2 - An application to the Atherosclerosis Risk in Communities (ARIC) study
AU - Kang, Sangwook
AU - Cai, Jianwen
AU - Chambless, Lloyd
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013/1
Y1 - 2013/1
N2 - In the case-cohort studies conducted within the Atherosclerosis Risk in Communities (ARIC) study, it is of interest to assess and compare the effect of high-sensitivity C-reactive protein (hs-CRP) on the increased risks of incident coronary heart disease and incident ischemic stroke. Empirical cumulative hazards functions for different levels of hs-CRP reveal an additive structure for the risks for each disease outcome. Additionally, we are interested in estimating the difference in the risk for the different hs-CRP groups. Motivated by this, we consider fitting marginal additive hazards regression models for case-cohort studies with multiple disease outcomes. We consider a weighted estimating equations approach for the estimation of model parameters. The asymptotic properties of the proposed estimators are derived and their finite-sample properties are assessed via simulation studies. The proposed method is applied to analyze the ARIC Study.
AB - In the case-cohort studies conducted within the Atherosclerosis Risk in Communities (ARIC) study, it is of interest to assess and compare the effect of high-sensitivity C-reactive protein (hs-CRP) on the increased risks of incident coronary heart disease and incident ischemic stroke. Empirical cumulative hazards functions for different levels of hs-CRP reveal an additive structure for the risks for each disease outcome. Additionally, we are interested in estimating the difference in the risk for the different hs-CRP groups. Motivated by this, we consider fitting marginal additive hazards regression models for case-cohort studies with multiple disease outcomes. We consider a weighted estimating equations approach for the estimation of model parameters. The asymptotic properties of the proposed estimators are derived and their finite-sample properties are assessed via simulation studies. The proposed method is applied to analyze the ARIC Study.
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U2 - 10.1093/biostatistics/kxs025
DO - 10.1093/biostatistics/kxs025
M3 - Article
C2 - 22826550
AN - SCOPUS:84871233233
VL - 14
SP - 28
EP - 41
JO - Biostatistics
JF - Biostatistics
SN - 1465-4644
IS - 1
ER -