cccrm (version 3.0.4)

cccUst: Repeated Measures Concordance Correlation Coefficient estimated by U-statistics

Description

Estimation of the concordance correlation coefficient for repeated measurements using the U-statistics approach. The function is also applicable for the non-repeated measurements scenario.

Usage

cccUst(dataset, ry, rmet, rtime = NULL, Dmat = NULL, delta = 1, cl = 0.95)

Value

A vector that includes the point estimate, confidence interval and standard error of the CCC. Additionally the Fisher's Z-transformation value and its standard error are also provided.

Arguments

dataset

An object of class data.frame.

ry

Character string. Name of the outcome in the data set.

rmet

Character string. Name of the method variable in the data set.

rtime

Character string. Name of the time variable in the data set.

Dmat

Matrix of weights.

delta

Power of the differences. A value of 0 provides an estimate that is comparable to a repeated measures version of kappa index.

cl

Confidence level.

References

King, TS and Chinchilli, VM. (2001). A generalized concordance correlation coefficient for continuous and categorical data. Statistics in Medicine, 20, 2131:2147.King, TS; Chinchilli, VM; Carrasco, JL. (2007). A repeated measures concordance correlation coefficient. Statistics in Medicine, 26, 3095:3113.Carrasco, JL; Phillips, BR; Puig-Martinez, J; King, TS; Chinchilli, VM. (2013). Estimation of the concordance correlation coefficient for repeated measures using SAS and R. Computer Methods and Programs in Biomedicine, 109, 293-304.

Examples

# Non-longitudinal scenario
newdat=bpres[bpres$NM==1,]
estccc=cccUst(newdat,"DIA","METODE")
estccc

estccc=cccUst(bdaw,"AUC","MET","VNUM")
estccc

estccc=cccUst(bfat,"BF","MET","VISITNO",Dmat=diag(c(2,1,1)))
estccc