Bayesian superposition of pure-birth destructive cure processes for tumor latency

DOI10.1080/03610918.2018.1538455zbMath1489.62354OpenAlexW2900914377WikidataQ128901601 ScholiaQ128901601MaRDI QIDQ5083939

Josemar Rodrigues, Adriano K. Suzuki, Fernando Raimundo da Silva, Marco Henrique de Almeida Inacio, Narayanaswamy Balakrishnan

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2018.1538455

zbMATH Keywords

Bayesian estimationfrailty modelssurvival functionsYule processshort-term effectsCox regression modelspure-birth processesdestructive random variableslong-term effectsStan sampler

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Bayesian inference (62F15) Medical applications (general) (92C50)

Cites Work

• A stochastic two-stage carcinogenesis model: A new approach to computing the probability of observing tumor in animal bioassays
• A Semiparametric Approach for the Two-Sample Comparison of Survival Times with Long-Term Survivors
• A New Bayesian Model for Survival Data with a Surviving Fraction
• Semiparametric analysis of short-term and long-term hazard ratios with two-sample survival data
• Bayesian survival analysis
• Identifiability of cure models
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Bayesian superposition of pure-birth destructive cure processes for tumor latency