Advances and Applications in Statistics
Volume 46, Issue 2, Pages 107 - 117
(August 2015) http://dx.doi.org/10.17654/ADASAug2015_107_117 |
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ANALYSIS OF SURVIVAL DATA BY USING NON-PARAMETRIC METHODS
Medhat Mohamed Ahmed Abdelaal and Sally Hossam Eldin Ahmed
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Abstract: Statistical techniques such as Kaplan-Meier product limit estimate which take into account censored data are mainly used in the medical and biological sciences for estimating the probability of failure in time-to-event data “survival data”. The main objective of this paper is to estimate the survival function of Egyptian patients performed liver transplantation operation due to liver diseases by using K-M estimate. The present study showed the 1 year survival after LDLT was 85.76% with mean survival time 10.504 months, however, the 2 year survival after LDLT was 81.45% with mean survival time 20.584 months. Also, the data showed that higher MELD score has a definitely higher risk of death after LDLT. The log-rank test showed that there is a statistically significant difference in survival functions for MELD score groups. |
Keywords and phrases: survival analysis, censoring, Kaplan-Meier estimate, log-rank test, living donor liver transplantation (LDLT), model for end stage liver disease (MELD). |
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