Smooth confidence intervals for the survival function under random right censoring

Abstract

The present article presents a methodological advance which contributes to the area of nonparametric survival analysis under random right censoring. The central idea is to develop pointwise confidence intervals for the survival function by means of a central limit theorem for an, already existing in the literature, kernel smooth survival estimate. Numerical simulations reveal the progress in coverage accuracy offered by the suggested confidence intervals over the proposals already existing in the literature.