PROreg: Patient Reported Outcomes Regression Analysis

It offers a wide variety of techniques, such as graphics, recoding, or regression models, for a comprehensive analysis of patient-reported outcomes (PRO). Especially novel is the broad range of regression models based on the beta-binomial distribution useful for analyzing binomial data with over-dispersion in cross-sectional, longitudinal, or multidimensional response studies (see Najera-Zuloaga J., Lee D.-J. and Arostegui I. (2019) <doi:10.1002/bimj.201700251>).

Version: 1.3
Imports: fmsb, car, RColorBrewer, matrixcalc, rootSolve, numDeriv, Matrix
Published: 2024-03-13
DOI: 10.32614/CRAN.package.PROreg
Author: Josu Najera-Zuloaga, Dae-Jin Lee, Inmaculada Arostegui
Maintainer: Josu Najera-Zuloaga <josu.najera at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: PROreg results


Reference manual: PROreg.pdf


Package source: PROreg_1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): PROreg_1.3.tgz, r-oldrel (arm64): PROreg_1.3.tgz, r-release (x86_64): PROreg_1.3.tgz, r-oldrel (x86_64): PROreg_1.3.tgz
Old sources: PROreg archive

Reverse dependencies:

Reverse suggests: insight, parameters


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