On Accelerated Failure Time Models Performance Under Progressive Type-II Censoring

Abstract

Accelerated failure time (AFT) models have intensive applications in many research areas, including but not limited to behavioral, chronic (e.g., cancer), and infectious diseases (e.g., HIV) research. In this paper, we investigate the performance of the AFT models when Progressive Type-II censoring schemes are performed. We demonstrate the usefulness of using these schemes. We discuss their testing procedure power, $Bias$, and $MSE$ of the hazard ratio estimates compared to the same sample size of the uncensored data. Theoretically, we derive the models, the $MLE$ scores, and the Fisher information matrix. A comparison between these estimators is provided by using extensive simulation. A real-life data example is provided to illustrate our proposed estimators.