Statistics and Its Interface

Volume 14 (2021)

Number 3

A model checking method for the additive hazards model with multivariate current status data

Pages: 309 – 321

DOI: https://dx.doi.org/10.4310/20-SII639

Authors

Yanqin Feng (School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, China)

Cheng Zhang (School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, China)

Jieli Ding (School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, China)

Abstract

This paper presents a class of graphical and numerical techniques to check the overall fitting adequacy of the marginal additive hazards model to multivariate current status data. The proposed testing methods are based on the supremum of the stochastic processes derived from the cumulative sum of martingale-based residuals over time and covariates. The distributions of the proposed stochastic processes can be approximated via a simulation technique. A series of simulation studies are conducted to assess the finite-sample performance of the proposed methods. An application to a data set from a tumorigenicity study is provided.

Keywords

interval-censored data, model checking, additive hazards model

Full Text (PDF format)

This research is supported in part by the National Natural Science Foundation of China (11471252 to Y.F., 11671310 to J.D.).

Received 22 September 2019

Accepted 23 September 2020

Published 9 February 2021