Bayes analysis of the generalized gamma AFT models for left truncated and right censored data

• Published in: Journal of statistical computation and simulation 2023-08, Vol.93 (12), p.2026-2051
• Main Authors: Shukla, Asmita, Ranjan, Rakesh, Upadhyay, Satyanshu K.
• Format: Article
• Language: English
• Subjects: accelerated failure time model; Acquired immune deficiency syndrome; AIDS; Algorithms; Bayes factor; Censored data (mathematics); Datasets; Failure times; gamma distribution; Generalized gamma distribution; highly active antiretroviral therapy; Langevin algorithm; Mathematical models; Metropolis-Hastings algorithm; weibull distribution
• ISSN: 0094-9655; 1563-5163
• DOI: 10.1080/00949655.2023.2172169

This article considers the Bayes analysis of generalized gamma accelerated failure time model and its two components Weibull and gamma when the given observations are left truncated and right censored. In order to perform the analysis, the paper proposes the use of an improved version of the Metropolis-Hastings algorithm, namely, the Metropolis-adjusted Langevin algorithm. Besides, the paper also checks the model compatibility and compares the considered models with its components using the Bayes factor computed on the basis of a recent methodology. A numerical illustration is provided based on a simulated as well as a real dataset. The real dataset consists of individuals infected with human immunodeficiency virus who are at the risk of acquired immunodeficiency syndrome and subsequent deaths. The numerical illustration is further extended to check the effect of different therapies including the highly active antiretroviral therapy on the lifetime of individuals.