icc: Intraclass correlation coefficient (ICC)

In psy: Various Procedures Used in Psychometrics

Intraclass correlation coefficient (ICC)

Description

Computes the ICC of several series of measurements, for example in an interrater agreement study. Two types of ICC are proposed: consistency and agreement.

Usage

icc(data)

Arguments

data	n*p matrix or dataframe, n subjects p raters

Details

Missing data are omitted in a listwise way. The "agreement" ICC is the ratio of the subject variance by the sum of the subject variance, the rater variance and the residual; it is generally prefered. The "consistency" version is the ratio of the subject variance by the sum of the subject variance and the residual; it may be of interest when estimating the reliability of pre/post variations in measurements.

Value

A list with :

$nb.subjects	number of subjects under study
$nb.raters	number of raters
$subject.variance	subject variance
$rater.variance	rater variance
$residual	residual variance
$icc.consistency	Intra class correlation coefficient, "consistency" version
$icc.agreement	Intra class correlation coefficient, "agreement" version

Author(s)

Bruno Falissard

References

Shrout, P.E., Fleiss, J.L. (1979), Intraclass correlation: uses in assessing rater reliability, Psychological Bulletin, 86, 420-428.

Examples

data(expsy)
icc(expsy[,c(12,14,16)])

#to obtain a 95%confidence interval:
#library(boot)
#icc.boot <- function(data,x) {icc(data[x,])[[7]]}
#res <- boot(expsy[,c(12,14,16)],icc.boot,1000)
#quantile(res$t,c(0.025,0.975))  # two-sided bootstrapped confidence interval of icc (agreement)
#boot.ci(res,type="bca")         # adjusted bootstrap percentile (BCa) confidence interval (better)

psy documentation built on April 22, 2022, 1:08 a.m.