Title: Estimation of bivariate survival functions: A simulation study on the effects of sample size
Authors: Marialuisa Restaino - University of Salerno (Italy) [presenting]
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. Moreover, due to missing information related to censoring and truncation, it becomes crucial to have an adequate sample size, to have a significant estimate of the bivariate survival function. Starting from this background, after reviewing the most used estimators for the bivariate survival function, when both components are censored and truncated, we will inspect the effects of different sample sizes of the bivariate survival functions, according to some censoring percentages and truncation probabilities. By a simulation study and application to real datasets, we will test the influence of sample sizes on the performance of the estimators.