Regression analysis of dependent current status data with the accelerated failure time model

Abstract

In this article, we discuss the regression analysis of dependent current status data under the accelerated failure time model. There exist many literatures discussing the regression analysis of current status data under different models, but few literature discussing the regression problem of dependent current status data under the AFT model. Corresponding to this, we propose a sieve maximum likelihood approach for estimation of covariate effects. In the approach, we model the correlation between the interested survival time and the observation time by the copula function. Simulation study is conducted in order to assess the finite sample behavior of the method. A real data example is provided to illustrate the application of the proposed method.

KEYWORDS:

• Accelerated failure time model
• Bernstein polynomial
• Current status data
• Informative censoring

Acknowledgments

We wish to thank the Editor, the Associate Editor and two reviewers for their many helpful comments.

Additional information

Funding

Xu’s work was partially supported by the Fundamental Research Funds for the Central Universities (2412020QD026). Zhao’s work was partially supported by the National Natural Science Foundation of China (NSFC) (11671168) and the Science and Technology Developing Plan of Jilin Province (No. 20200201258JC).