Modelos hierárquicos aplicados a dados biológicos de contagem

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: Henriques, Marcos Jardel
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual de Maringá
Brasil
Departamento de Estatística
Programa de Pós-Graduação em Bioestatística
UEM
Maringá, PR
Centro de Ciências Exatas
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.uem.br:8080/jspui/handle/1/4367
Resumo: A database from an experiment with two groups of 15 Nelore cows (Bos Tauros indicus) was analyzed. One group received a control supplementation (treatment 1) and the other received a supplementation with inclusion of long chain fatty acids salts (treatment 2). The data has the amount of aspirated and viable oocytes in a total of collects ranging from 2 to 8 aspirations per cow in a 120 days experiment, approximately. The objective of this study was to evaluate possible differences between treatments in relation to oocytes quantity and viability produced, as well as to identify best fit models through the Frequent, Bayesian and Bayesiana Longitudinal approaches. We used some hierarchical models and probability distributions. It was possible to conclude that there was no significant difference between treatments by the three approaches. In addition, by the Frequentist analysis, the best adjustments were made, respectively, by Binomial-Negative, Beta-Binomial and Poisson-Generalized models. In Bayesian analysis, the best adjustments were the Binomial, Beta-Binomial, Binomial-Negative, Poisson-Generalized and Binomial-Poisson-Generalized models. On the other hand, by the Bayesian Longitudinal approach, all models were adequate.