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Models for lifetime data in the presence of competing causes with different activation mechanisms

Grant number: 11/22924-4
Support type:Scholarships abroad - Research
Effective date (Start): July 02, 2012
Effective date (End): July 01, 2013
Field of knowledge:Physical Sciences and Mathematics - Probability and Statistics - Statistics
Principal researcher:Vicente Garibay Cancho
Grantee:Vicente Garibay Cancho
Host: Dipak Kumar Dey
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Research place: University of Connecticut (UCONN), United States  

Abstract

In this project we propose new models for survival data with and without a fraction of cure. The proposed models arise in a scenario of latent competitive causes (risks), where the number of causes (latent variable) for the occurrence of a particular event of interest is modelled by a power series distribution. For the proposed models, we develop inferential procedures from classical and Bayesian perspectives.Classical inferential approach is based on the likelihood method. From the Bayesian point of view however we explore the use of Monte Carlo methods (MCMC). (AU)

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