ISSN: 0970-938X (Print) | 0976-1683 (Electronic)

Biomedical Research

An International Journal of Medical Sciences

Abstract

Methodological Comparison of Survival Analysis Methods in Censored Medical Data

Right censored data is the type of data in which the interested event has not been observed in working period determined initially; or which is arisen in case that any information cannot be taken from a person in the study after a certain period. In this study, it is purposed that survival probabilities of right censored data have been calculated and compared by Kaplan-Meier product limit method (K-M), life table method and exponential and Weibull Distribution methods. The sample has been generated by a simulation basing on data obtained from a research on a chronic illness in a healthcare organization. R Studio software (R Studio Team (2015) has been used in producing dataset. In dataset, there are survival periods and censor states regarding two new treatment methods. The difference between patients’ survival periods has been analysed by according to nonparametric K-M product limit method, semi parametric life table method and parametric exponential and Weibull distribution methods. When methods are compared with each other, nonparametric K-M product limit method estimator informs about the best prediction for current sample. When prediction method is evaluated according to exponential distribution parameters which require parametric assumption, a considerably approximate result to K-M product limit method has been obtained. Using the appropriate statistical analysis method is one of the most fundamental tools for achieving the right information. Physicians making decisions based on accurate information will increase the patient benefit in a medical and ethical way, and will also make a significant contribution to the success of medicine.

Author(s): Ayse Canan Yazici Guvercin, Mustafa Agah Tekindal, Ozlem Kaymaz, Cemal Huseyin Guvercin
Abstract | Full-Text | PDF

Share this  Facebook  Twitter  LinkedIn  Google+