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cccrm  

Concordance Correlation Coefficient for Repeated (and Non-Repeated) Measures
View on CRAN: Click here


Download and install cccrm package within the R console
Install from CRAN:
install.packages("cccrm")

Install from Github:
library("remotes")
install_github("cran/cccrm")

Install by package version:
library("remotes")
install_version("cccrm", "2.2.2")



Attach the package and use:
library("cccrm")
Maintained by
Josep Lluis Carrasco
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-10-04
Latest Update: 2022-08-31
Description:
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) and Carrasco et al. (2013) .
How to cite:
Josep Lluis Carrasco (2011). cccrm: Concordance Correlation Coefficient for Repeated (and Non-Repeated) Measures. R package version 2.2.2, https://cran.r-project.org/web/packages/cccrm
Previous versions and publish date:
1.0 (2011-10-04 12:09), 1.1 (2012-04-10 12:05), 1.2.1 (2015-07-08 00:52), 2.0.1 (2020-06-10 14:00), 2.0.2 (2021-04-16 15:00), 2.0.3 (2021-04-29 01:20), 2.1.0 (2022-08-31 19:30), 2.2.0 (2023-10-26 14:00), 2.2.1 (2024-01-12 15:10)
Other packages that cited cccrm R package
View cccrm citation profile
Other R packages that cccrm depends, imports, suggests or enhances
Functions, R codes and Examples using the cccrm R package
Some associated functions: bdaw . bfat . bpres . cccUst . ccclon . ccclonw . cccvc . icc . 
Some associated R codes: bdiag.R . cccUst.R . ccclon.R . ccclonw.R . cccvc.R . cccvc1.R . cccvc2.R . extra_func.R . ic.ccc.R . ic.icc.R . icc.R . phi.R . print.ccc.R . print.cccUst.R . print.icc.R . summary.ccc.R . summary.icc.R .  Full cccrm package functions and examples
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