meanrho: Mean of bivariate rank correlations between raters

Description

Computes the mean of bivariate Spearman's rho rank correlations between raters as an index of the interrater reliability of ordinal data.

Usage

meanrho(ratings, fisher = TRUE)

Arguments

ratings

n*m matrix or dataframe, n subjects m raters.

fisher

a logical indicating whether the correlation coefficients should be Fisher z-standardized before averaging.

Value

A list with class '"irrlist"' containing the following components:

$method

a character string describing the method applied for the computation of interrater reliability.

$subjects

the number of subjects examined.

$raters

the number of raters.

$irr.name

a character string specifying the name of the coefficient.

$value

coefficient of interrater reliability.

$stat.name

a character string specifying the name of the corresponding test statistic.

$statistic

the value of the test statistic.

$p.value

the p-value for the test.

$error

a character specifying whether correlations were dropped before the computation of the Fisher z-standardized average. Additionally, a warning message is created if ties were found within raters.

Details

Missing data are omitted in a listwise way. The mean of bivariate rank correlations should not be used as an index of interrater reliability when ties within raters occur. The null hypothesis r=0 could only be tested when Fisher z-standardized values are used for the averaging. When computing Fisher z-standardized values, perfect correlations are omitted before averaging because z equals +/-Inf in that case.

Examples

Run this code

# NOT RUN {
data(anxiety)
meanrho(anxiety, TRUE)
# }