Package: cccrm 3.0.4

Josep Lluis Carrasco

cccrm: Concordance Correlation Coefficient for Repeated (and Non-Repeated) Measures

Estimates the Concordance Correlation Coefficient to assess agreement. The scenarios considered are non-repeated measures, non-longitudinal repeated measures (replicates) and longitudinal repeated measures. It also includes the estimation of the one-way intraclass correlation coefficient also known as reliability index. The estimation approaches implemented are variance components and U-statistics approaches. Description of methods can be found in Fleiss (1986) <doi:10.1002/9781118032923> and Carrasco et al. (2013) <doi:10.1016/j.cmpb.2012.09.002>.

Authors:Josep Lluis Carrasco [aut, cre], Gonzalo Peon Pena [aut]

cccrm_3.0.4.tar.gz
cccrm_3.0.4.tar.gz(r-4.5-noble)cccrm_3.0.4.tar.gz(r-4.4-noble)
cccrm_3.0.4.tgz(r-4.4-emscripten)cccrm_3.0.4.tgz(r-4.3-emscripten)
cccrm.pdf |cccrm.html✨
cccrm/json (API)
NEWS

# Install 'cccrm' in R:
install.packages('cccrm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • bdaw - Blood draw data
  • bfat - Body fat data
  • bpres - Blood pressure data

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.30 score 876 downloads 5 mentions 11 exports 46 dependencies

Last updated 1 months agofrom:1d83fd580f. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 09 2025
R-4.5-linuxOKMar 09 2025
R-4.4-linuxOKMar 09 2025

Exports:ccc_estccc_est_by_timeccc_sim_dataccc_vcccclonccclonwcccUstcccvclme_modelsim_power_cccZtest

Dependencies:clicodetoolscolorspacecpp11Derivdigestdplyrfansifarverfurrrfuturegenericsggplot2globalsgluegtableisobandlabelinglatticelifecyclelistenvmagrittrMASSMatrixmgcvmunsellnlmenlmeUparallellypillarpkgconfigprogressrpurrrR6RColorBrewerrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr