Method of model checking for case II interval-censored data under the additive hazards model

Abstract

General or case II interval-censored data are commonly encountered in practice. We develop methods for model-checking and goodness-of-fit testing for the additive hazards model with case II interval-censored data. We propose test statistics based on the supremum of the stochastic processes derived from the cumulative sum of martingale-based residuals over time and covariates. We approximate the distribution of the stochastic process via a simulation technique to conduct a class of graphical and numerical techniques for various purposes of model-fitting evaluations. Simulation studies are conducted to assess the finite-sample performance of the proposed method. A real dataset from an AIDS observational study is analyzed for illustration.