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Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R

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Parsons, Nicholas R., Costa, Matthew L., Achten, Juul and Stallard, Nigel (2009) Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R. Computational Statistics & Data Analysis, Vol.53 (No.3). pp. 632-641. doi:10.1016/j.csda.2008.08.004

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Official URL: http://dx.doi.org/10.1016/j.csda.2008.08.004

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Abstract

The widely used proportional odds model is developed for correlated repeated ordinal score data, using a modified version of the generalized estimating equation (GEE) method for model fitting for a range of working correlation models. The algorithm developed estimates the correlation parameter, by minimizing the generalized variance of the regression parameters at each step of the fitting algorithm. Methods for parameter estimation are described for the widely used uniform and first-order autoregressive correlation models, for data potentially recorded at irregularly spaced time intervals. A full implementation of the algorithm (repolr) in the R statistical software package, that both tests the assumption of proportional odds and accommodates missing data, is described and applied to a clinical trial of post-operative treatment, after rupture of the Achilles tendon and a study of patient pain response after hip joint resurfacing. (C) 2008 Elsevier B. V. All rights reserved.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
R Medicine > RD Surgery
Divisions: Faculty of Medicine > Warwick Medical School > Health Sciences
Faculty of Medicine > Warwick Medical School
Faculty of Medicine > Warwick Medical School > Health Sciences > Clinical Trials Unit
Library of Congress Subject Headings (LCSH): Generalized estimating equations, Regression analysis -- Computer programs, Algorithms, Clinical trials -- Mathematical models, Postoperative care -- Mathematical models
Journal or Publication Title: Computational Statistics & Data Analysis
Publisher: Elsevier Science Ltd
ISSN: 0167-9473
Official Date: 15 January 2009
Dates:
DateEvent
15 January 2009Published
Volume: Vol.53
Number: No.3
Number of Pages: 10
Page Range: pp. 632-641
DOI: 10.1016/j.csda.2008.08.004
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access

Data sourced from Thomson Reuters' Web of Knowledge

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