SAKTHIVEL, E (2021) SURVIVAL ANALYSIS FOR DIAGNOSING TUBERCULOSIS PATIENTS. Stochastic Modeling and Applications, 25 (1). pp. 35-43. ISSN 0972-3641

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The nature of survival analysis is modeling of time to failure considering the time until death or failure. Kaplan-Meier estimate is one of the
best options used to measure the portion of subjects who living for a certain
period of time after treatment. This technique is extremely useful in survival
analysis at the same time it is used by the researchers to determine or analyze the patients who lost to follow up of the study, those who developed
the disease of attention or survived it. It’s also used to comparation two
group of subjects such as the control group, ie., placebo, and the other treatment group ie., true drug. This context was devised to analyze the Log-rank
(Mantel-Cox) distribution that has been comparative to the Survival time
serving as Gender and Treatment diagnose the prognostic cause patients for
survival time of the patients. In this paper, the treatment indicated a significant difference, while gender has not shown any significant difference in
the survival of the Tuberculosis (TB) patients. The SPSS software package
performs information analysis.

Item Type: Article
Uncontrolled Keywords: Survival Analysis, Censoring, Kaplan-Meier Estimator, Log Rank Test, Cox Proportional Hazards Model, Tuberculosisand Biostatistics.
Divisions: PSG College of Arts and Science > Department of Statistics
Depositing User: Mr Team Mosys
Date Deposited: 01 Apr 2022 09:54
Last Modified: 01 Apr 2022 09:54

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