Literature DB >> 8804143

Effect of dropouts in a longitudinal study: an application of a repeated ordinal model.

E Lesaffre1, G Molenberghs, L Dewulf.   

Abstract

An analysis is presented of a longitudinal study of fluvoxamine, an antidepressant drug, with ordinal responses, regressed on a combination of discrete and continuous covariates and with a substantial proportion of dropouts. Classical methods, such as weighted least squares (SAS procedure CATMOD) and logistic regression, are not suitable for the analysis of such data. Instead, we illustrate how a recently introduced model can be used to solve most of the problems posed. The method is likelihood-based and is an extension of the bivariate Dale model to an arbitrary number of outcomes. The method is suitable for several types of designs commonly employed in clinical trials.

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Year:  1996        PMID: 8804143     DOI: 10.1002/(SICI)1097-0258(19960615)15:11<1123::AID-SIM228>3.0.CO;2-L

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

1.  Semiparametric regression models and sensitivity analysis of longitudinal data with nonrandom dropouts.

Authors:  David Todem; Kyungmann Kim; Jason Fine; Limin Peng
Journal:  Stat Neerl       Date:  2010-05-01       Impact factor: 1.190

2.  The use of Sandimmun (cyclosporin A) in severe refractory rheumatoid arthritis: the Belgian experience.

Authors:  M G Malaise; P De Keyser; M De Backer; M A van Lierde; E Lesaffre
Journal:  Clin Rheumatol       Date:  1995-09       Impact factor: 2.980

3.  A global sensitivity test for evaluating statistical hypotheses with nonidentifiable models.

Authors:  D Todem; J Fine; L Peng
Journal:  Biometrics       Date:  2009-07-23       Impact factor: 2.571

  3 in total

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