Análise de dados longitudinais para variáveis binárias
The objective of this work is to present techniques of regression analysis for longitudinal data when the response variable is binary. Initially, there is a review of generalized linear models, marginal models, transition models, mixed models, and logistic regression methods of estimation, which wil...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2009 |
| País: | Brasil |
| Institución: | Universidade Federal de São Carlos (UFSCAR) |
| Repositorio: | Repositório Institucional da UFSCAR |
| Idioma: | portugués |
| OAI Identifier: | oai:repositorio.ufscar.br:20.500.14289/4531 |
| Acceso en línea: | https://repositorio.ufscar.br/handle/20.500.14289/4531 |
| Access Level: | acceso abierto |
| Palabra clave: | Análise de regressão Regressão logística Estatística - estudos longitudinais Modelos lineares generalizados Modelos lineares (Estatística) Dados longitudinais Modelos marginais Equação de estimação generalizada Longitudinal data Generalized linear models Marginal models Transition models Models mixtos Binary variables Logistic regression Generalized estimating equation CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA::ESTATISTICA |
| Sumario: | The objective of this work is to present techniques of regression analysis for longitudinal data when the response variable is binary. Initially, there is a review of generalized linear models, marginal models, transition models, mixed models, and logistic regression methods of estimation, which will be necessary for the development of work. In addition to the methods of estimation, some structures of correlation will be studied in an attempt to capture the intra-individual serial dependence over time. These methods were applied in two situations, one where the response variable is continuous and normal distribution, and another when the response variable has the Bernoulli distribution. It was also sought to explore and present techniques for selection of models and diagnostics for the two cases. Finally, an application of the above methodology will be presented using a set of real data. |
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