iccCounts: Intraclass Correlation Coefficient for Count Data

Estimates the intraclass correlation coefficient (ICC) for count data to assess repeatability (intra-methods concordance) and concordance (between-method concordance). In the concordance setting, the ICC is equivalent to the concordance correlation coefficient estimated by variance components. The ICC is estimated using the estimates from generalized linear mixed models. The within-subjects distributions considered are: Poisson; Negative Binomial with additive and proportional extradispersion; Zero-Inflated Poisson; and Zero-Inflated Negative Binomial with additive and proportional extradispersion. The statistical methodology used to estimate the ICC with count data can be found in Carrasco (2010) <doi:10.1111/j.1541-0420.2009.01335.x>.

Version: 1.0.3
Depends: R (≥ 4.0)
Imports: glmmTMB, ggplot2, Deriv, gridExtra, VGAM, dplyr
Suggests: knitr, rmarkdown
Published: 2021-07-30
Author: Josep L. Carrasco
Maintainer: Josep L. Carrasco <jlcarrasco at ub.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: iccCounts results


Reference manual: iccCounts.pdf
Vignettes: Examples of assessment of agreement with count data
Package source: iccCounts_1.0.3.tar.gz
Windows binaries: r-devel: iccCounts_1.0.3.zip, r-release: iccCounts_1.0.3.zip, r-oldrel: iccCounts_1.0.3.zip
macOS binaries: r-release (arm64): iccCounts_1.0.3.tgz, r-release (x86_64): iccCounts_1.0.3.tgz, r-oldrel: iccCounts_1.0.3.tgz
Old sources: iccCounts archive


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