Journal
JOURNAL OF MULTIVARIATE ANALYSIS
Volume 100, Issue 2, Pages 278-290Publisher
ELSEVIER INC
DOI: 10.1016/j.jmva.2008.04.012
Keywords
Association; Binary outcomes; Clustered data; Estimating equation; Marginal mean; Semiparametric estimation; Undersmooth
Categories
Funding
- NHLBI NIH HHS [N01HC25195] Funding Source: Medline
- NIAID NIH HHS [R01 AI059773, N01AI50020, R01 AI059773-03, R01 AI062247, R01 AI062247-03, R01 AI059773-01A2, R01 AI059773-02, R01 AI062247-01, R01 AI062247-02] Funding Source: Medline
Ask authors/readers for more resources
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 relatively little work concerning both the marginal and association structures, especially in the semiparametric framework. In this paper, our interest centers on the inference of both the marginal and association parameters. We develop a semiparametric method for clustered binary data and establish the theoretical results. The proposed methodology is investigated through various numerical studies. (C) 2008 Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available