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sklarsomega: Measuring Agreement Using Sklar's Omega Coefficient

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

Documentation:

Reference manual: sklarsomega.pdf

Downloads:

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

Linking:

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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.