Comparison of Different Parametric Modelling for Child Dengue Patients: A Survival Approach

V. Raghul Gandhi¹ , R. Nandhinidevi² , R. Reka³ , K. Saravanaraj⁴ , Saravanan G.⁵

Section:Research Paper, Product Type: Journal-Paper
Vol.8 , Issue.4 , pp.47-53, Aug-2021

Online published on Aug 31, 2021

Copyright © V. Raghul Gandhi, R. Nandhinidevi, R. Reka, K. Saravanaraj, Saravanan G. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Survival Analysis is one of the important statistical procedures which are mainly used to analyze the time to event data in various fields such as Public Health, Medicine, Political Science, Biostatistics and Epidemiology etc. A Parametric and Non-Parametric method plays a vital role in building a survival model for many diseases. In this paper these parametric models were applied to the data of 109 child dengue patients. The primary goal of this paper is to study the parametric survival models such as Exponential distribution, Weibull distribution, Gompertz distribution and some life time distributions and distribution free Methods such as Kaplan Meier Estimator and Log-Rank test for the dengue data and to compare the best model among Parametric methods by using model measurement criterion as the best model fit is identified by smaller AIC, BIC value and Non Parametric methods is used to examine the survival curves of the Dengue patients. As a result, Logistic distribution is found to be best model. The Statistical Analysis is done by using Statistical software such as IBM SPSS Statistics 21 and R i386 3.6.3 language.

Key-Words / Index Term :
Survival Analysis, Parametric methods, Distribution free methods, AIC and BIC.

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