A0858
Title: Goodness-of-fit testing with survival data
Authors: Jacobo de Una-Alvarez - University of Vigo (Spain) [presenting]
Juan Carlos Escanciano - Universidad Carlos III de Madrid (Spain)
Abstract: The aim is to present a new general strategy for goodness-of-fit testing with survival data. The setting is that of testing for a parametric family of distribution functions when the data deteriorates due to random censoring and/or random truncation. A key step is the characterization of the null hypothesis through a moment equation, which involves the estimation of the observable distribution under both the null and the alternative. An omnibus test based on a maximum mean discrepancy principle will be proposed, and its theoretical properties will be presented. The finite sample performance of the proposed test will be investigated through simulations. Illustrative real-data applications will be given.
