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

dc.contributor.authorAsmita Shukla
dc.contributor.authorRakesh Ranjan
dc.contributor.authorSatyanshu K. Upadhyay
dc.date.accessioned2026-02-07T11:40:54Z
dc.date.issued2023
dc.description.abstractThis 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. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
dc.identifier.doi10.1080/00949655.2023.2172169
dc.identifier.issn949655
dc.identifier.urihttps://doi.org/10.1080/00949655.2023.2172169
dc.identifier.urihttps://dl.bhu.ac.in/bhuir/handle/123456789/46510
dc.publisherTaylor and Francis Ltd.
dc.subjectaccelerated failure time model
dc.subjectBayes factor
dc.subjectgamma distribution
dc.subjectGeneralized gamma distribution
dc.subjecthighly active antiretroviral therapy
dc.subjectLangevin algorithm
dc.subjectMetropolis-Hastings algorithm
dc.subjectweibull distribution
dc.titleBayes analysis of the generalized gamma AFT models for left truncated and right censored data
dc.typePublication
dspace.entity.typeArticle

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