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Provides tools for applying the Bayesian Gower agreement methodology (presented in the package vignette) to nominal or ordinal data. The framework can accommodate any number of units, any number of coders, and missingness; and can handle both one-way and two-way random study designs. Influential units and/or coders can be identified easily using leave-one-out statistics.
| Version: | 1.0-1 |
| Depends: | R (≥ 3.5.0) |
| Suggests: | testthat |
| Published: | 2024-09-10 |
| DOI: | 10.32614/CRAN.package.goweragreement |
| Author: | John Hughes [aut, cre] |
| Maintainer: | John Hughes <drjphughesjr at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://www.johnhughes.org |
| NeedsCompilation: | no |
| CRAN checks: | goweragreement results |
| Reference manual: | goweragreement.pdf |
| Package source: | goweragreement_1.0-1.tar.gz |
| Windows binaries: | r-devel: goweragreement_1.0-1.zip, r-release: goweragreement_1.0-1.zip, r-oldrel: goweragreement_1.0-1.zip |
| macOS binaries: | r-release (arm64): goweragreement_1.0-1.tgz, r-oldrel (arm64): goweragreement_1.0-1.tgz, r-release (x86_64): goweragreement_1.0-1.tgz, r-oldrel (x86_64): goweragreement_1.0-1.tgz |
| Old sources: | goweragreement 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.