Nonparametric estimation from proportional hazards competing risks data under selection bias
Brownian motion, Cross-sectional sampling, Gateaux-differential process, Length bias, Martingale representation, Stochastic integral, Weak convergence
Journal of Nonparametric Statistics
In many practical situations, such as cross-sectional sampling, the observed random sample suffers from selection bias in the sense that it does not represent the target population. This paper considers the problem of estimating the target survivor function when the data for two independent competing risks having proportional hazards is observed under such a selection bias. The large sample behavior of the proposed estimator is studied through martingale representation and stochastic integrals. © 2005 Taylor & Francis Group Ltd.
Department of Mathematics
Original Publication Date
DOI of published version
Dauxois, Jean Yves; Guilloux, Agathe; and Kirmani, Syed N.U.A., "Nonparametric estimation from proportional hazards competing risks data under selection bias" (2005). Faculty Publications. 2919.