Proportional hazards model under ranked setsampling scheme using censored data of coronaryheart disease

Abstract

The proportional hazards model is one of the most common model for analyzing survivaldata. Only proportional hazards assumption is required to apply this model. Using ap-propriate sampling methods is an important part of modelling data and estimation ofparameters. In literature there is a few studies based on sampling methods in survivalanalysis and most of them are related with non-parametric estimations of survival func-tions, sample size calculation etc. The main innovation of our approach is to examinethe sampling methods for the proportional hazards model. This paper describes usage ofranked set sampling design in the proportional hazards model. In order to analyze theperformance of our methods, we use a real data and conduct a simulation study. Weconclued that ranked set sampling is more efficient than simple random sampling.