Modelagem de dados de sobrevivência com eventos recorrentes via fragilidade discreta

• Ano de defesa: 2015
• Autor(a) principal: Macera, Márcia Aparecida Centanin
• Orientador(a): Louzada Neto, Francisco
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Estatística - PPGEs
• Palavras-chave em Português: Análise de sobrevivência; Eventos recorrentes; Processo de Poisson; Fragilidade discreta; Máxima verossimilhança
• Palavras-chave em Inglês: Survival analysis; Recurrent events; Poisson process; Maximum likelihood; Discrete frailty
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA::ESTATISTICA::FUNDAMENTOS DA ESTATISTICA
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/7574

In this thesis it is proposed alternative methodologies and extensions on models for recurrent event data. Speci cally, we propose a model in which the distribution of the gap time is easily derived from the marginal rate function providing more direct practical interpretation besides to consider the relation between successive gap times for each individual. Another model that extends the frailty models for recurrent event data to allow a Bernoulli, Geometric, Poisson, Discrete Weibull, Negative Binomial or other discrete distribution of the frailty variable has also been proposed. The parameter estimation procedure for both models was conducted considering maximum likelihood methods. Simulation studies were performed in order to examine some frequentist properties of the estimation method and evaluate the maximum likelihood estimates quality. Real data applications demonstrated the use of the proposed models. Overall, the proposed models were suitable for analyzing recurrent event data.