Survival analysis of dialysis patients under parametric and non-parametric approaches

Maryam Siddiqa, Mueen Ud Din Azad, Muhammad Khalid Pervaiz, Muhammad Ghias, Gulzar H. Shah, Uzma Hafeez

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Abstract

Dialysis is a life saving procedure and recommended way of treatment for end stage kidney diseases. Transplantation can also be useful source but it is restricted by financial limitations especially in developing countries like Pakistan. A little work has been done in literature regarding the estimated survival time of dialysis patients in Pakistan. So, this study has estimated the median survival time of male/females patients separately by parametric and nonparametric approaches. Moreover, comparison of survival time to patients (≤ 50 years and >50 years) was also compared. As censoring is an important part of the survival data which causes insensitivity to the usual procedures of analysis. Frequently, in modeling the survival data, most of the time we have no prior information about the theoretical distribution of survival time, that's why, nonparametric methods are commonly used. The significance of this study is the fitting of probability distribution of real life time data of dialysis patients which is not done before. It is very laborious job to fit an appropriate distribution of the data and estimation of parameters. We find that the probability distribution of our real life time data is weibull distribution. Finding suggested that the Kaplan-Meier method and weibull model based on Anderson-Darling test provided a very close estimate of the survival function in both genders and age groups. On the average survival time in males is relatively high but not statistically different from females.

Original languageEnglish
Pages (from-to)271-288
Number of pages18
JournalElectronic Journal of Applied Statistical Analysis
Volume5
Issue number2
StatePublished - 2012

Scopus Subject Areas

  • Statistics and Probability
  • Modeling and Simulation

Keywords

  • Dialysis
  • Kaplan-Meier method
  • Non-parametric tests
  • Parametric tests
  • Survival data
  • Weibull distribution

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