cccvc: Concordance Correlation Coefficient estimated by Variance...

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

Concordance Correlation Coefficient estimated by Variance Components

Description

Estimation of the concordance correlation coefficient for non-repeated measurements and non-longitudinal repeated measurements (replicates) using the variance components from a linear mixed model. The appropriate intraclass correlation coefficient is used as estimator of the concordance correlation coefficient.

Usage

cccvc(
  dataset,
  ry,
  rind,
  rmet,
  covar = NULL,
  int = FALSE,
  cl = 0.95,
  control.lme = list()
)

Arguments

dataset	an object of class data.frame.
ry	Character string. Name of the outcome in the data set.
rind	Character string. Name of the subject variable in the data set.
rmet	Character string. Name of the method variable in the data set.
covar	Character vector. Name of covariates to include in the linear mixed model as fixed effects.
int	Binary indicating if the subject-method interaction has to be included in the model when analyzing the non-longitudinal setting (defaults to FALSE).
cl	Confidence level.
control.lme	A list of control values for the estimation algorithm used in lme function. For further details see lme help.

Details

This function has been deprecated. See ccc_vc.

cccrm documentation built on June 8, 2025, 11:23 a.m.