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 ehu.eus>
License:	GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation:	no
CRAN checks:	PROreg results

Documentation:

Reference manual:

PROreg.pdf

Downloads:

Package source:	PROreg_1.3.tar.gz
Windows binaries:	r-devel: PROreg_1.3.zip, r-release: PROreg_1.3.zip, r-oldrel: PROreg_1.3.zip
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

Linking:

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