Computes the mean of bivariate Pearson's product moment correlations between raters as an index of the interrater reliability of quantitative data.
meancor(ratings, fisher = TRUE)n*m matrix or dataframe, n subjects m raters.
a logical indicating whether the correlation coefficients should be Fisher z-standardized before averaging.
A list with class '"irrlist"' containing the following components:
a character string describing the method applied for the computation of interrater reliability.
the number of subjects examined.
the number of raters.
a character string specifying the name of the coefficient.
coefficient of interrater reliability.
a character string specifying the name of the corresponding test statistic.
the value of the test statistic.
the p-value for the test.
a character string specifying whether correlations were dropped before the computation of the Fisher z-standardized average.
Missing data are omitted in a listwise way. The mean of bivariate correlations should not be used as an index of interrater reliability when the variance of ratings differs between raters. 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.
# NOT RUN {
data(anxiety)
meancor(anxiety)
# }
Run the code above in your browser using DataLab