title: Proportional hazards model with varying coefficients for length-biased data.
abstract: Length-biased data arise in many important applications including epidemiological cohort studies, cancer prevention trials and studies of labor economics. Such data are also often subject to right censoring due to loss of follow-up or the end of study. In this paper, we consider a proportional hazards model with varying coefficients for right-censored and length-biased data, which is used to study the interact effect nonlinearly of covariates with an exposure variable. A local estimating equation method is proposed for the unknown coefficients and the intercept function in the model. The asymptotic properties of the proposed estimators are established by using the martingale theory and kernel smoothing techniques. Our simulation studies demonstrate that the proposed estimators have an excellent finite-sample performance. The Channing House data is analyzed to demonstrate the applications of the proposed method.
authors: School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China.
authors: Feipeng
authors: F
authors: Zhang
authors: Xuerong
authors: X
authors: Chen
authors: Yong
authors: Y
authors: Zhou
mesh_terms: D000368:Aged; D015982:Bias; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D016016:Proportional Hazards Models; D012179:Retirement
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