Analysis of Correlated Binary Data under Partially Linear Logistic Models

Clustered data arise commonly in practice and it is often of interest to estimate the mean response parameters as well as the association parameters. However, most research has been directed to address the mean response parameters with the association parameters relegated to a nuisance role. There is little work concerning both the marginal and association structures, especially in the semiparametric framework. In this paper, our interest centers on inference on both the marginal and association parameters, which is driven by many practical applications. We develop semiparametric methods for clustered binary data and establish the theoretical results. The proposed methodology is investigated through various numerical studies.