Hypothesis testing of hazard ratio parameters in marginal models for multivariate failure time data.
Marginal hazard models for multivariate failure time data have been studied extensively in recent literature. However, standard hypothesis test statistics based on the likelihood method are not exactly appropriate for this kind of model. In this paper, extensions of the three commonly used likelihood hypothesis test statistics are discussed. Generalized Wald, generalized score and generalized likelihood ratio tests for hazard ratio parameters in a marginal hazard model for multivariate failure time data are proposed and their asymptotic distributions examined. The finite sample properties of these statistics are studied through simulations. The proposed method is applied to data from Busselton Population Health Surveys.
Cai
J
J
University of North Carolina at Chapel Hill, USA.
D000367:Age Factors; D001794:Blood Pressure; D015992:Body Mass Index; D002784:Cholesterol; D003198:Computer Simulation; D005260:Female; D006306:Health Surveys; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008954:Models, Biological; D015999:Multivariate Analysis; D016016:Proportional Hazards Models; D012907:Smoking; D013997:Time Factors
D002784:Cholesterol