A new cure rate frailty regression model based on a weighted Lindley distribution applied to stomach cancer data

In this paper, we propose a new cure rate frailty regression model based on a two-parameter weighted Lindley distribution. The weighted Lindley distribution has attractive properties such as flexibility on its probability density function, Laplace transform function on closed-form, among others. An...

Full description

Saved in:
Bibliographic Details
Published in:Statistical methods & applications 2023-09, Vol.32 (3), p.883-909
Main Authors: Mota, Alex, Milani, Eder A., Leão, Jeremias, Ramos, Pedro L., Ferreira, Paulo H., Junior, Oilson G., Tomazella, Vera L. D., Louzada, Francisco
Format: Article
Language:English
Subjects:
Cancer
Chemistry and Earth Sciences
Computer Science
Economics
Finance
Frailty
Gastric cancer
Health Sciences
Heterogeneity
Humanities
Insurance
Laplace transforms
Law
Management
Mathematics and Statistics
Maximum likelihood estimation
Maximum likelihood estimators
Medicine
Monte Carlo simulation
Original Paper
Parameter identification
Physics
Probability density functions
Regression models
Statistical analysis
Statistical inference
Statistical Theory and Methods
Statistics
Statistics for Business
Statistics for Engineering
Statistics for Life Sciences
Statistics for Social Sciences
Stomach
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we propose a new cure rate frailty regression model based on a two-parameter weighted Lindley distribution. The weighted Lindley distribution has attractive properties such as flexibility on its probability density function, Laplace transform function on closed-form, among others. An advantage of proposed model is the possibility to jointly model the heterogeneity among patients by their frailties and the presence of a cured fraction of them. To make the model parameters identifiable, we consider a reparameterized version of the weighted Lindley distribution with unit mean as frailty distribution. The proposed model is very flexible in sense that has some traditional cure rate models as special cases. The statistical inference for the model’s parameters is discussed in detail using the maximum likelihood estimation under random right-censoring. Further, we present a Monte Carlo simulation study to verify the maximum likelihood estimators’ behavior assuming different sample sizes and censoring proportions. Finally, the new model describes the lifetime of 22,148 patients with stomach cancer, obtained from the Fundação Oncocentro de São Paulo, Brazil.
ISSN:1618-2510
1613-981X
DOI:10.1007/s10260-022-00673-y