title: Proportional hazards model with a change point for clustered event data.
abstract: In many epidemiology studies, family data with survival endpoints are collected to investigate the association between risk factors and disease incidence. Sometimes the risk of the disease may change when a certain risk factor exceeds a certain threshold. Finding this threshold value could be important for disease risk prediction and diseases prevention. In this work, we propose a change-point proportional hazards model for clustered event data. The model incorporates the unknown threshold of a continuous variable as a change point in the regression. The marginal pseudo-partial likelihood functions are maximized for estimating the regression coefficients and the unknown change point. We develop a supremum test based on robust score statistics to test the existence of the change point. The inference for the change point is based on the m out of n bootstrap. We establish the consistency and asymptotic distributions of the proposed estimators. The finite-sample performance of the proposed method is demonstrated via extensive simulation studies. Finally, the Strong Heart Family Study dataset is analyzed to illustrate the methods.
authors.affiliation: Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, U.S.A.
authors.forename: Yu
authors.initials: Y
authors.lastname: Deng
authors.affiliation: Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, U.S.A.
authors.forename: Donglin
authors.initials: D
authors.lastname: Zeng
authors.affiliation: Department of Epidemiology, Tulane University, New Orleans, Louisiana, U.S.A.
authors.forename: Jinying
authors.initials: J
authors.lastname: Zhao
authors.affiliation: Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, U.S.A.
authors.forename: Jianwen
authors.initials: J
authors.lastname: Cai
mesh_terms: D016000:Cluster Analysis; D016013:Likelihood Functions; D016016:Proportional Hazards Models; D012307:Risk Factors
keywords: Change point; Clustered event; Proportional hazards model; m out of n bootstrap