Extended generalized Marshall–Olkin model for dependent censoring

Abstract In this paper, we consider dependent competing risks using the Extended Marshall–Olkin model, where observation times are subject to censoring. The probabilistic properties of the survival copula associated with this model are examined, along with its application to the analysis of censored data. An estimation strategy using Bernstein polynomials for marginal distributions and joint survival probabilities is developed. The asymptotic normality of the proposed estimators is established under appropriate regularity conditions. The effectiveness of the proposed methodology is assessed through a simulation study using synthetic datasets and further validated with an application to real‐world data.