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Joint regression and association modeling of longitudinal ordinal data

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), pp. 795-803. (doi:10.1111/j.0006-341X.2003.00093.x).

Record type: Article


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.

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Published date: 2003


Local EPrints ID: 34761
PURE UUID: 774cde44-cbba-4a0c-9396-bae81a0c8def
ORCID for Peter W.F. Smith: ORCID iD

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Date deposited: 17 May 2006
Last modified: 17 Jul 2017 15:49

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

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