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Marginal regression analysis of multivariate binary response

Marginal regression analysis of multivariate binary response
Marginal regression analysis of multivariate binary response
We propose the use of the mean parameter for regression analysis of a multivariate binary response. We model the association using dependence ratios defined in terms of the mean parameter, the components of which are the joint success probabilities of all orders. This permits flexible modelling of higher-order associations, using maximum likelihood estimation. We reanalyse two data sets, one with variable cluster size and the other a longitudinal data set with constant cluster size.
0006-3444
847-854
Ekholm, Anders
bc4d2421-5d0d-4250-b8e1-adddf60772e7
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
McDonald, John W.
9adae16e-e1e1-4ddf-bf4c-7231ee8c1c8e
Ekholm, Anders
bc4d2421-5d0d-4250-b8e1-adddf60772e7
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
McDonald, John W.
9adae16e-e1e1-4ddf-bf4c-7231ee8c1c8e

Ekholm, Anders, Smith, Peter W.F. and McDonald, John W. (1995) Marginal regression analysis of multivariate binary response. Biometrika, 82 (4), 847-854. (doi:10.1093/biomet/82.4.847).

Record type: Article

Abstract

We propose the use of the mean parameter for regression analysis of a multivariate binary response. We model the association using dependence ratios defined in terms of the mean parameter, the components of which are the joint success probabilities of all orders. This permits flexible modelling of higher-order associations, using maximum likelihood estimation. We reanalyse two data sets, one with variable cluster size and the other a longitudinal data set with constant cluster size.

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Published date: November 1995

Identifiers

Local EPrints ID: 34310
URI: http://eprints.soton.ac.uk/id/eprint/34310
DOI: doi:10.1093/biomet/82.4.847
ISSN: 0006-3444
PURE UUID: cb74cf3a-7960-48b5-90d5-6c8f2b5c392f
ORCID for Peter W.F. Smith: ORCID iD orcid.org/0000-0003-4423-5410

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Date deposited: 18 Jan 2008
Last modified: 16 Mar 2024 02:42

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Contributors

Author: Anders Ekholm
Author: Peter W.F. Smith ORCID iD
Author: John W. McDonald

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