A Nonparametric Test for Comparing Cumulative Incidence Functions of Current Status Competing Risks Data

Abstract

In survival or reliability studies, current status censoring is common where the exact life time of patients (objects) is unobservable, but one can only observe a monitoring time and whether the event of interest has happened or not before the monitoring time. In addition, when patients (objects) are exposed to the risk of failure due to two or more causes, we also observe the cause of failure for relapsed patients. Competing risks data with current status censoring arise frequently from cross-sectional studies in demography, epidemiology, and reliability studies. In this article, we propose a nonparametric test for comparing cumulative incidence functions of current status competing risks data. Asymptotic distribution of the test statistic is derived. A simulation study is conducted to assess the finite sample behavior of the test statistic. The practical utility of the procedure is well demonstrated using a real-life data set on menopausal history of 2423 women given in Jewell et al. (2003).

AMS Subject Classifications:

• 62N03

Keywords:

• Chernoff’s distribution
• Chi-square test
• Competing risks data
• Current status censoring

Acknowledgments

We thank the editor and referee for their valuable comments, which helped to improve the article.

Funding

The first author thanks the University Grants Commission, India, for financial support.