A proportional-hazards model for survival analysis and long-term survivors modeling: application to amyotrophic lateral sclerosis data

DOI10.1080/02664763.2020.1830954OpenAlexW3093456081MaRDI QIDQ5085643

Soufiane Gasmi, Tasnime Hamdeni

Publication date: 27 June 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2020.1830954

zbMATH Keywords

parameter estimationamyotrophic lateral sclerosisproportional-hazardsdefective modeling

Mathematics Subject Classification ID

Linear inference, regression (62Jxx) Applications of statistics to biology and medical sciences; meta analysis (62P10) Parametric inference (62Fxx) Survival analysis and censored data (62Nxx) Applications of statistics (62Pxx) Statistical distribution theory (62Exx)

Cites Work

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• The generalized Gompertz distribution
• Mixture and Non-Mixture Cure Fraction Models Based on Generalized Gompertz Distribution under Bayesian Approach
• The Marshall–Olkin extended generalized Lindley distribution: Properties and applications
• A new method for adding a parameter to a family of distributions with application to the exponential and Weibull families
• Improvements on Cross-Validation: The .632+ Bootstrap Method
• A multivariate Gompertz-type distribution
• Zero-adjusted defective regression models for modeling lifetime data
• Defective models induced by gamma frailty term for survival data with cured fraction
• Marshall–Olkin frailty survival models for bivariate right-censored failure time data
• EM algorithm-based likelihood estimation for a generalized Gompertz regression model in presence of survival data with long-term survivors: an application to uterine cervical cancer data
• Parameter estimation of the flexible Weibull distribution for type I censored samples
• Defective regression models for cure rate modeling with interval‐censored data
• Modelling geographically referenced survival data with a cure fraction
• Estimating the turning point of the log-logistic hazard function in the presence of long-term survivors with an application for uterine cervical cancer data

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