repolr
swMATH ID:  7133 
Software Authors:  Parsons, Nick R.; Costa, Matthew L.; Achten, Juul; Stallard, Nigel 
Description:  R package repolr: Repeated Measures Proportional Odds Logistic Regression. Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R. 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 firstorder 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 postoperative treatment, after rupture of the Achilles tendon and a study of patient pain response after hip joint resurfacing. 
Homepage:  http://cran.rproject.org/web/packages/repolr/index.html 
Source Code:  https://github.com/cran/repolr 
Dependencies:  R 
Related Software:  R; geepack; multgee; SAS; PROC GENMOD; SPSS; CopulaModel; MICE; catdata; VineCopula; nlme; CRTgeeDR; wgeesel; robust; PMM; PoisNor; VGAM; gnm; weightedScores; mprobit 
Cited in:  11 Publications 
Standard Articles
1 Publication describing the Software, including 1 Publication in zbMATH  Year 

Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R. Zbl 1452.62840 Parsons, Nick R.; Costa, Matthew L.; Achten, Juul; Stallard, Nigel 
2009

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Cited by 34 Authors
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Cited in 7 Serials
Cited in 3 Fields
11  Statistics (62XX) 
2  Numerical analysis (65XX) 
1  Computer science (68XX) 