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Multivariate modeling of survival data and quality-of-life issues in survival analysis

Grant number: 12/17886-9
Support type:Scholarships abroad - Research
Effective date (Start): January 16, 2013
Effective date (End): July 18, 2013
Field of knowledge:Physical Sciences and Mathematics - Probability and Statistics - Statistics
Principal Investigator:Antonio Carlos Pedroso de Lima
Grantee:Antonio Carlos Pedroso de Lima
Host: Pranab Kumar Sen
Home Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Local de pesquisa : University of North Carolina at Chapel Hill (UNC), United States  

Abstract

The project considers two topics. In the first one relates to the gamma frailty model, one of the most popular models to deal with dependent survival data. It has been extensively explored in the literature. In this paper we examine in which extent contiguity can be used when we are interested in testing regressor and frailtyparameters simultaneously. Based on that we examine how to establish the asymptotic distribution for the corresponding maximum likelihood estimators and test statistics, evaluating the power of tests related to the dependence parameter taking into consideration that fact that under the null hypothesis, the parameter lies on the border of the parameter space. The second topic relates to the development of methods to deal with the so-called quality adjusted survival lifetime (QALY), that considers survival times that can be negative and are subject to informative censoring. (AU)