Adjusted Kaplan-Meier Survival Estimator Ranks for a Set of Medical Data

Abstract

This study proposes to provide four methods for the purpose of adjusting the Ranks of the Kaplan-Meier survival function estimation, which are considered alternative non-parametric estimates of the grouped censored data, thus producing estimates for us are the Rank-Adjusted Estimator, the Liechtenstein Estimator, the Smith-Waterman Estimator and the Histogram Estimator, in the Applied side a simulation system was designed for the purpose of generating grouped censored data of three sizes ( 50, 80, 100) for the purpose of calculating the survival function estimate for three sample sizes and comparison with the Kaplan-Meier estimate, which acts as a reference model, and then calculating performance measures the task shows that the Histogram Estimator comes in first place for all sample sizes followed by the Liechtenstein Estimator by increasing the sample size.