Regression analysis of informatively interval-censored failure time data with semiparametric linear transformation model

ABSTRACT

Regression analysis of interval-censored failure time data with noninformative censoring has been widely investigated and many methods have been proposed. Sometimes the mechanism behind the interval censoring may be informative and several approaches have also been developed for this latter situation. However, all of these existing methods are for single models and it is well known that in many situations, one may prefer more flexible models. Corresponding to this, the linear transformation model is considered and a maximum likelihood estimation method is established. In the proposed method, the association between the failure time of interest and the censoring time is modelled by the copula model, and the involved nonparametric functions are approximated by spline functions. The large sample properties of the proposed estimators are derived. Numerical results show that the proposed method performs well in practical application. Besides, a real data example is presented for the illustration.

KEYWORDS:

• Interval-censored data
• linear transformation model
• copula models
• informative censoring
• splines
• efficient estimation

Acknowledgments

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

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work described in the paper was partially supported by the National Science Foundation of China grants 11671168 (Zhao) and 11671274 (Hu), Science and Technology Developing Plan of Jilin Province (No. 20170101061JC, Zhao), and Support Project of High-level Teachers in Beijing Municipal Universities in the Period of 13th Five-year Plan (No. CIT & TCD 201804078, Hu).