Proportional hazards model under ranked set sampling scheme using censored data of coronary heart disease

Year 2020, Volume: 49 Issue: 1, 458 - 477, 06.02.2020

Nursel Koyuncu , Nihal Ata Tutkun

https://doi.org/10.15672/hujms.617303

Cited By: 1

Abstract

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

Keywords

Cox regression, likelihood function, censored data, ranked set sampling

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