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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 |
| 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 |
Please use the canonical form https://CRAN.R-project.org/package=PROreg to link to this page.
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.
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