An Application of Exponential-Lindley Distribution in Modelling Cancer Survival Data

G Jayakodi; N Sundaram; P Venkatesan

doi:10.17485/IJST/v15i46.1870

Article

An Application of Exponential-Lindley Distribution in Modelling Cancer Survival Data

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Indian Journal of Science and Technology

DOI: 10.17485/IJST/v15i46.1870

Year: 2022, Volume: 15, Issue: 46, Pages: 2579-2588

Original Article

An Application of Exponential-Lindley Distribution in Modelling Cancer Survival Data

G Jayakodi^1*, N Sundaram², P Venkatesan³

¹Research Scholar, Department of Statistics, Presidency College,, Chennai, Tamil Nadu, India
²Assistant Professor, Department of Statistics, Presidency College, Tamil Nadu India, Chennai
³Department of Statistics, National Institute for Research in Tuberculosis (ICMR), Chennai, Tamil Nadu, India

*Corresponding Author
Email: [email protected]

Received Date:15 September 2022, Accepted Date:22 October 2022, Published Date:14 December 2022

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Objective: To explore multiple myeloma cancer survival data using the Exponential-Lindley model and compare the performance with other related models. Methods: In this article both simulated and real data sets were used for comparison. The model parameters are estimated for real and simulated data sets using the maximum likelihood method. The real data sets consist of 48 Cancer patients with multiple myeloma with 25% of them was censored observations. We consider both type I and type II censoring mechanism with 5%, 10% and 20% censoring. The performance was compared using three measures Deviance, AIC and BIC. Findings: The performance of Exponential-Lindley model was compared with related models Exponential, Lindley, Power Lindley, Gamma, and Burr-XII models. Simulated and real data sets are applied in the underlying models. The Exponential-Lindley model outperformed compared to other models. Novelty: The new model is novel alternative for modelling censored survival data for different levels and types of censoring.

Keywords: Cancer survival; Censoring; Simulation; ExpG family; Exponential Lindley Model

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Copyright

© 2022 Jayakodi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)