Estimação e diagnóstico em modelos multivariados para dados censurados

Author(s)

Larissa Avila Matos

• Document type: Doctoral Thesis
• Press: Campinas, SP.
• Institution: Universidade Estadual de Campinas (UNICAMP). Instituto de Matemática, Estatística e Computação Científica
• Defense date: 2016-05-30

Examining board members

Víctor Hugo Lachos Dávila; Mariana Rodrigues Motta; Filidor Edilfonso Vilca Labra; Gilberto Alvarenga Paula; Clecio da Silva Ferreira

• Advisor: Víctor Hugo Lachos Dávila

Abstract

In some acquired immunodeficiency syndrome (AIDS) clinical trials, the human immunodeficiency virus-1 ribonucleic acid measurements are collected irregularly over time and are often subject to some upper and lower detection limits, depending on the quantification assays. Hence, these responses are either left- or right-censored. In practice, longitudinal data coming from those follow-up studies can be modelled using censored linear and nonlinear mixed-effects models and also censored regression models with a specific correlation structures on the error terms. A complication arises when more than one series of responses are repeatedly collected on each subject at irregularly occasions over a period of time. The multivariate censored linear mixed model is a frequently used tool for a joint analysis of more than one series of longitudinal data. In this thesis we develop a series of essays in which different models and techniques to deal with censored data are applied. As result, we had several works to carry out censored data (AU)

• FAPESP's process: 11/22063-9 - APPLICATIONS OF THE SCALE MIXTURES OF SKEW-NORMAL DISTRIBUTIONS IN FACTOR ANALYSIS MODELS
• Grantee: Larissa Avila Matos
• Support Opportunities: Scholarships in Brazil - Doctorate