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Implements Bayesian data analyses of balanced repeatability and reproducibility studies with ordinal measurements. Model fitting is based on MCMC posterior sampling with 'rjags'. Function ordinalRR() directly carries out the model fitting, and this function has the flexibility to allow the user to specify key aspects of the model, e.g., fixed versus random effects. Functions for preprocessing data and for the numerical and graphical display of a fitted model are also provided. There are also functions for displaying the model at fixed (user-specified) parameters and for simulating a hypothetical data set at a fixed (user-specified) set of parameters for a random-effects rater population. For additional technical details, refer to Culp, Ryan, Chen, and Hamada (2018) and cite this Technometrics paper when referencing any aspect of this work. The demo of this package reproduces results from the Technometrics paper.
| Version: | 1.1 |
| Depends: | R (≥ 2.10), rjags |
| Suggests: | graphics |
| Published: | 2020-03-30 |
| DOI: | 10.32614/CRAN.package.ordinalRR |
| Author: | Ken Ryan |
| Maintainer: | Ken Ryan <kjryan at mail.wvu.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Citation: | ordinalRR citation info |
| CRAN checks: | ordinalRR results |
| Reference manual: | ordinalRR.pdf |
| Package source: | ordinalRR_1.1.tar.gz |
| Windows binaries: | r-devel: ordinalRR_1.1.zip, r-release: ordinalRR_1.1.zip, r-oldrel: ordinalRR_1.1.zip |
| macOS binaries: | r-release (arm64): ordinalRR_1.1.tgz, r-oldrel (arm64): ordinalRR_1.1.tgz, r-release (x86_64): ordinalRR_1.1.tgz, r-oldrel (x86_64): ordinalRR_1.1.tgz |
| Old sources: | ordinalRR archive |
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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.