Additive risks regression model for middle censored exponentiated-exponential lifetime data

ABSTRACT

Jammalamadaka and Mangalam introduced middle censoring which refers to data arising in situations, where the exact lifetime becomes unobservable if it falls within a random censoring interval. In the present article, we propose an additive risks regression model for a lifetime data subject to middle censoring, where the lifetimes are assumed to follow exponentiated exponential distribution. The regression parameters are estimated using the Expectation-Maximization algorithm. Asymptotic normality of the estimator is proposed. We report a simulation study to assess the finite sample properties of the estimator. We then analyze a real-life data on survival times of larynx cancer patients studied by Karduan.

KEYWORDS:

• Additive risks model
• EM algorithm
• Middle censoring

MATHEMATICS SUBJECT CLASSIFICATION:

• 62N01
• 62N02

Acknowledgment

We thank the editor and anonymous referees for their constructive comments on the article.