NON-PARAMETRIC METHODS FOR COMPARING TWO SURVIVAL DISTRIBUTIONS

Authors

  • M. Ramakrishnan Department of Mathematics RKM Vivekananda College, Chennai, India
  • R. Ravanan Department of Statistics, Presidency College, Chennai, India

Keywords:

Survival Probabilities, Non-Parametric test, Kaplan-Meier estimate, Log-rank test, Cox-Mantel test

Abstract

Survival curves for each group gives comparison at some arbitrary point(s) but it does not provide a comparison of the total survival experience of two groups. So some Non-parametric methods like log rank test, Cox-Mantel test are popular methods used for comparing the survival distribution and also these methods takes whole follow-up period. In this paper non-parametric methods are used for data from WHAS.

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References

Altman DG, Bland JM.( 1998),” Time to event (survival) data”. British Medical Journal (BMJ); vol. 317: pp. 468-469.

Altman DG, Bland JM.( 1998), “Survival probabilities (The Kaplan-Meier method)”. BMJ; vol. 317; pp. 1572 - 1580.

Altman DG, Bland JM. (2004),” The log rank Test”, BMJ; vol. 328 ; pp. 1073.

Collett D. (2003), “Modeling of Survival Data in Medical Research”. Chapman Hall, London, U.K.

Elisa T. Lee. (1992), “Statistical methods for Survival Data Analysis”. Second Edition. A Wiley-Inter science publication, United States of America.

Kaplan, E. L., and Paul Meier (Jun. 1958),” Non parametric Estimation from Incomplete Observations”, Journal of the American Statistical Association. Vol. 53, pp457 – 481.

Rupert G. Miller J R (1981), “Survival Analysis”, John Wiley & Sons, United States of America.

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Published

19-09-2021

How to Cite

M. Ramakrishnan, & R. Ravanan. (2021). NON-PARAMETRIC METHODS FOR COMPARING TWO SURVIVAL DISTRIBUTIONS. Researchers World - International Refereed Social Sciences Journal, 4(2), 121–125. Retrieved from https://www.researchersworld.com/index.php/rworld/article/view/1046

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