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Provides tools for applying Sklar's Omega (Hughes, 2018) <doi:10.48550/arXiv.1803.02734> methodology to nominal scores, ordinal scores, percentages, counts, amounts (i.e., non-negative real numbers), and balances (i.e., any real number). The framework can accommodate any number of units, any number of coders, and missingness; and can be used to measure agreement with a gold standard, intra-coder agreement, and/or inter-coder agreement. Frequentist inference is supported for all levels of measurement. Bayesian inference is supported for continuous scores only.
Version: | 3.0-2 |
Imports: | extraDistr, hash, LaplacesDemon, Matrix, mcmcse, numDeriv, spam, dfoptim |
Suggests: | lattice, parallel, pbapply |
Published: | 2023-04-04 |
DOI: | 10.32614/CRAN.package.sklarsomega |
Author: | John Hughes |
Maintainer: | John Hughes <drjphughesjr at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
CRAN checks: | sklarsomega results |
Reference manual: | sklarsomega.pdf |
Package source: | sklarsomega_3.0-2.tar.gz |
Windows binaries: | r-devel: sklarsomega_3.0-2.zip, r-release: sklarsomega_3.0-2.zip, r-oldrel: sklarsomega_3.0-2.zip |
macOS binaries: | r-release (arm64): sklarsomega_3.0-2.tgz, r-oldrel (arm64): sklarsomega_3.0-2.tgz, r-release (x86_64): sklarsomega_3.0-2.tgz, r-oldrel (x86_64): sklarsomega_3.0-2.tgz |
Old sources: | sklarsomega 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.