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https://www.arca.fiocruz.br/handle/icict/54567
MARGINAL MODELS FOR THE ASSOCIATION STRUCTURE OF HIERARCHICAL BINARY RESPONSES
Author
Affilliation
ABG Consultoria. Belo Horizonte, Brazil
Universidade Federal de Minas Gerais. Departamento de Estatística. Belo Horizonte, MG, Brazil
Universidade Estadual de Feira de Santana. Feira de Santana, BA, Brasil/Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, Brazil
Universidade Federal de Minas Gerais. Departamento de Estatística. Belo Horizonte, MG, Brazil
Universidade Federal da Bahia. Departamento de Estatística. Salvador, BA, Brazil
Universidade Federal de Minas Gerais. Departamento de Estatística. Belo Horizonte, MG, Brazil
Universidade Estadual de Feira de Santana. Feira de Santana, BA, Brasil/Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, Brazil
Universidade Federal de Minas Gerais. Departamento de Estatística. Belo Horizonte, MG, Brazil
Universidade Federal da Bahia. Departamento de Estatística. Salvador, BA, Brazil
Abstract
Clustered binary responses are often found in ecological studies. Data analysis may include modeling the marginal probability response. However, when the association is the main scientific focus, modeling the correlation structure between pairs of responses is the key part of the analysis. Second-order generalized estimating equations (GEE) are established in the literature. Some of them are more efficient in computational terms, especially facing large clusters. Alternating logistic regression (ALR) and orthogonalized residual (ORTH) GEE methods are presented and compared in this paper. Simulation results show a slightly superiority of ALR over ORTH. Marginal probabilities and odds ratios are also estimated and compared in a real ecological study involving a three-level hierarchical clustering. ALR and ORTH models are useful for modeling complex association structure with large cluster sizes.
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