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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 |
| Reference manual: | PROreg.pdf |
| 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 suggests: | insight, parameters |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.