A marginal mixed baseline hazards model for multivariate failure time data.
In multivariate failure time data analysis, a marginal regression modeling approach is often preferred to avoid assumptions on the dependence structure among correlated failure times. In this paper, a marginal mixed baseline hazards model is introduced. Estimating equations are proposed for the estimation of the marginal hazard ratio parameters. The proposed estimators are shown to be consistent and asymptotically Gaussian with a robust covariance matrix that can be consistently estimated. Simulation studies indicate the adequacy of the proposed methodology for practical sample sizes. The methodology is illustrated with a data set from the Framingham Heart Study.
Clegg
L X
LX
National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892-7352, USA. lin_clegg@nih.gov
Cai
J
J
Sen
P K
PK
D001699:Biometry; D003198:Computer Simulation; D003327:Coronary Disease / Q000209:etiology; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D016016:Proportional Hazards Models; D012044:Regression Analysis; D020521:Stroke / Q000209:etiology; D013997:Time Factors