Skip Navigation

Biometrika 2001 88(4):1121-1134; doi:10.1093/biomet/88.4.1121
© 2001 by Biometrika Trust
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Hoffman, E. B.
Right arrow Articles by Weinberg, C. R.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Within-cluster resampling

Elaine B.Hoffman1, Pranab K.Sen2 and Clarice R.Weinberg3

1 7 Janson Court, Westport, Connecticut 06880, U.S.Ameahoffman{at}aol.com 2 Department of Biostatistics, CB #7400, University of North Carolina, Chapel Hill, North Carolina 27599-7400, U.S.A.pksen{at}bios.unc.edu 3 National Institute of Environmental Health Sciences, P.O. Box 12233, MD A3-03, Research Triangle Park, North Carolina 27709, U.S.A. weinberg{at}niehs.nih.gov

Within-cluster resampling is proposed as a new method for analysing clustered data.Although the focus of this paper is clustered binary data, the within-cluster resampling asymptotic theory is general for many types of clustered data. Within-cluster resampling is a simple but computationally intensive estimation method. Its main advantage over other marginal analysis methods, such as generalised estimating equations (Liang & Zeger, 1986; Zeger & Liang, 1986) is that it remains valid when the risk for the outcome of interest is related to the cluster size, which we term nonignorable cluster size. We present theory for the asymptotic normality and provide a consistent variance estimator for the within-cluster resampling estimator. Simulations and an example are developed that assess the finite-sample behaviour of the new method and show that when both methods are valid its performance is similar to that of generalised estimating equations.

Key Words: Clustered binary data; Generalised estimating equations; Generalised linear model; Marginal model; Nonignorable cluster size; Resampling; Within-cluster correlation

Received May 1999. Revised May 2001


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Clin. Cancer Res.Home page
P. Monti, Y. Ciribilli, J. Jordan, P. Menichini, D. M. Umbach, M. A. Resnick, L. Luzzatto, A. Inga, and G. Fronza
Transcriptional Functionality of Germ Line p53 Mutants Influences Cancer Phenotype
Clin. Cancer Res., July 1, 2007; 13(13): 3789 - 3795.
[Abstract] [Full Text] [PDF]

Home page
 BiometrikaHome page
D. Larocque, J. Nevalainen, and H. Oja
A weighted multivariate sign test for cluster-correlated data
Biometrika, June 1, 2007; 94(2): 267 - 283.
[Abstract] [Full Text] [PDF]


Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.