Rank-based inference for the accelerated failure time model in the presence of interval censored data

• Main Authors: Karimi, Mostafa, Ibrahim, Noor Akma, Abu Bakar, Mohd Rizam, Arasan, Jayanthi
• Format: Conference or Workshop Item
• Language: English
• Published: AIP Publishing 2016
• Online Access: http://psasir.upm.edu.my/id/eprint/57161/1/Rank-based%20inference%20for%20the%20accelerated%20failure%20time%20model%20in%20the%20presence%20of%20interval%20censored%20data.pdf; http://psasir.upm.edu.my/id/eprint/57161/; http://aip.scitation.org/doi/abs/10.1063/1.4952568

Semiparametric analysis and rank-based inference for the accelerated failure time model are complicated in the presence of interval censored data. The main difficulty with the existing rank-based methods is that they involve estimating functions with the possibility of multiple roots. In this paper a class of asymptotically normal rank estimators is developed which can be aquired via linear programming for estimating the parameters of the model, and a two-step iterative algorithm is introduce for solving the estimating equations. The proposed inference procedures are assessed through a real example.