icc: Intraclass correlation coefficient (ICC) for oneway and...

In MAd: Meta-Analysis with Mean Differences

Intraclass correlation coefficient (ICC) for oneway and twoway models

Description

Computes single score or average score ICCs as an index of interrater reliability of quantitative data. Additionally, F-test and confidence interval are computed.

Usage

icc(ratings, model = c("oneway", "twoway"), 
    type = c("consistency", "agreement"), 
    unit = c("single", "average"), r0 = 0, conf.level = 0.95)

Arguments

ratings	n*m matrix or dataframe, n subjects m raters.
model	a character string specifying if a oneway model (default) with row effects random, or a twoway model with column and row effects random should be applied. You can specify just the initial letter.
type	a character string specifying if '"consistency"' (default) or '"agreement"' between raters should be estimated. If a '"oneway"' model is used, only '"consistency"' could be computed. You can specify just the initial letter.
unit	a character string specifying the unit of analysis: Must be one of single (default) or average. You can specify just the initial letter.
r0	specification of the null hypothesis r = r0. Note that a one sided test (H1: r > r0) is performed.
conf.level	confidence level of the interval.

Details

This function was created by Matthias Gamer for the irr package. For more details, see:

http://rss.acs.unt.edu/Rdoc/library/irr/html/icc.html

Details for the function:

Missing data are omitted in a listwise way. When considering which form of ICC is appropriate for an actual set of data, one has take several decisions (Shrout & Fleiss, 1979):

1. Should only the subjects be considered as random effects (oneway model) or are subjects and raters randomly chosen from a bigger pool of persons (twoway model).

2. If differences in judges' mean ratings are of interest, interrater agreement instead of consistency should be computed.

3. If the unit of analysis is a mean of several ratings, unit should be changed to average. In most cases, however, single values (unit = single) are regarded.

Value

A list with class icclist containing the following components:

subjects	the number of subjects examined.
raters	the number of raters.
model	a character string describing the selected model for the analysis.
type	a character string describing the selected type of interrater reliability.
unit	a character string describing the unit of analysis.
icc.name	a character string specifying the name of ICC according to McGraw & Wong (1996).
value	the intraclass correlation coefficient.
r0	the specified null hypothesis.
Fvalue	the value of the F-statistic.
df1	the numerator degrees of freedom.
df2	the denominator degrees of freedom.
p.value	the p-value for a two-sided test.
conf.level	the confidence level for the interval.
lbound	the lower bound of the confidence interval.
ubound	the upper bound of the confidence interval.

Author(s)

Matthias Gamer

References

Bartko, J.J. (1966). The intraclass correlation coefficient as a measure of reliability. Psychological Reports, 19, 3-11.

McGraw, K.O., & Wong, S.P. (1996), Forming inferences about some intraclass correlation coefficients. Psychological Methods, 1, 30-46.

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

Examples

# sample data

study <- c(1,1,2,2,3,3)
rater <- c(rep(1:2,3))
mod1 <- round(rnorm(6, 10, 1))
mod2 <- c(5,5, 9, 9, 8, 8)
mod3 <- c(10,10, 9, 9, 8, 8)
w <-data.frame(study, rater, mod1, mod2, mod3)
w


# if data is in this format:

# study rater mod1 mod2 mod3
#     1     1    9    9   10
#     1     2   11    8   10
#     2     1    9   10   11
#     2     2    9   10   11
#     3     1    9    9    8
#     3     2   12    9    8
#
# the data will need to be reshaped to be processed by the 
# icc function:

long <- reshape(w, varying=colnames(w)[3:5], v.names="Code", 
            idvar=c('study', 'rater'), timevar="mods", direction='long')
wide <- reshape(long, idvar=c('mods', 'study'), timevar='rater')

# icc function (created by Matthias Gamer for the 'irr' package)

icc(cbind(wide$Code.1, wide$Code.2), type= "consistency")

MAd documentation built on Aug. 7, 2022, 1:05 a.m.