Title: A comparison of nonparametric bivariate survival functions under censored and truncated data
Authors: Marialuisa Restaino - University of Salerno (Italy) [presenting]
Hongsheng Dai - University of Essex (United Kingdom)
Abstract: Bivariate survival data have received considerable attention recently. In survival analysis it is common to deal with incomplete information of the data, due to random censoring and random truncation. Most of the existing research focuses on bivariate survival analysis when components are either censoring or truncation or when one component is censored and truncated, but the other one is fully observed. Starting from this background, we will review the most used estimators for the bivariate survival function, when both components are censored and truncated. We will explain the differences between them, focusing on their main advantages and disadvantages. Thanks to a simulation study and application to real datasets, we will compare the performance of the estimators.