The University of Southampton
University of Southampton Institutional Repository

Joint regression and association modeling of longitudinal ordinal data

Joint regression and association modeling of longitudinal ordinal data
Joint regression and association modeling of longitudinal ordinal data
We propose models for longitudinal, or otherwise clustered, ordinal data. The association between subunit responses is characterized by dependence ratios (Ekholm, Smith, and McDonald, 1995, Biometrika82, 847–854), which are extended from the binary to the multicategory case. The joint probabilities of the subunit responses are expressed as explicit functions of the marginal means and the dependence ratios of all orders, obtaining a computational advantage for likelihood-based inference. Equal emphasis is put on finding regression models for the univariate cumulative probabilities, and on deriving the dependence ratios from meaningful association-generating mechanisms. A data set on the effects of treatment with Fluvoxamine, which has been analyzed in parts before (Molenberghs, Kenward, and Lesaffre, 1997, Biometrika84, 33–44), is analyzed in its entirety. Selection models are used for studying the sensitivity of the results to drop-out.
795-803
Ekholm, Anders
bc4d2421-5d0d-4250-b8e1-adddf60772e7
Jokinen, Jukka
7890f93a-e640-485e-9035-204eea758517
McDonald, John W.
9adae16e-e1e1-4ddf-bf4c-7231ee8c1c8e
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
Ekholm, Anders
bc4d2421-5d0d-4250-b8e1-adddf60772e7
Jokinen, Jukka
7890f93a-e640-485e-9035-204eea758517
McDonald, John W.
9adae16e-e1e1-4ddf-bf4c-7231ee8c1c8e
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940

Ekholm, Anders, Jokinen, Jukka, McDonald, John W. and Smith, Peter W.F. (2003) Joint regression and association modeling of longitudinal ordinal data. Biometrics, 59 (4), 795-803. (doi:10.1111/j.0006-341X.2003.00093.x).

Record type: Article

Abstract

We propose models for longitudinal, or otherwise clustered, ordinal data. The association between subunit responses is characterized by dependence ratios (Ekholm, Smith, and McDonald, 1995, Biometrika82, 847–854), which are extended from the binary to the multicategory case. The joint probabilities of the subunit responses are expressed as explicit functions of the marginal means and the dependence ratios of all orders, obtaining a computational advantage for likelihood-based inference. Equal emphasis is put on finding regression models for the univariate cumulative probabilities, and on deriving the dependence ratios from meaningful association-generating mechanisms. A data set on the effects of treatment with Fluvoxamine, which has been analyzed in parts before (Molenberghs, Kenward, and Lesaffre, 1997, Biometrika84, 33–44), is analyzed in its entirety. Selection models are used for studying the sensitivity of the results to drop-out.

This record has no associated files available for download.

More information

Published date: 2003

Identifiers

Local EPrints ID: 34761
URI: http://eprints.soton.ac.uk/id/eprint/34761
PURE UUID: 774cde44-cbba-4a0c-9396-bae81a0c8def
ORCID for Peter W.F. Smith: ORCID iD orcid.org/0000-0003-4423-5410

Catalogue record

Date deposited: 17 May 2006
Last modified: 16 Mar 2024 02:42

Export record

Altmetrics

Contributors

Author: Anders Ekholm
Author: Jukka Jokinen
Author: John W. McDonald

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×