Flexible models for hierarchical and overdispersed data in agriculture

• Ano de defesa: 2018
• Autor(a) principal: Sercundes, Ricardo Klein
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: B-spline; Beta distribution; Combined model; Distribuição beta; Distribuição multinomial; Generalized linear mixed model; Likelihood; Modelo combinado; Modelo linear generalizado misto; Multinomial distribution; Verossimilhança
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/11/11134/tde-01082018-154641/

In this work we explored and proposed flexible models to analyze hierarchical and overdispersed data in agriculture. A semi-parametric generalized linear mixed model was applied and compared with the main standard models to assess count data and, a combined model that take into account overdispersion and clustering through two separate sets of random effects was proposed to model nominal outcomes. For all models, the computational codes were implemented using the SAS software and are available in the appendix.