pvals.ICC2r.nointer function

P-values of ICC(2,1) under Model 2 without subject-rater interaction.

This function can compute several p-values associated with the Intraclass Correlation Coefficient (ICC) used to quantify inter-rater reliability under the random factorial ANOVA model without subject-rater interaction (Model 2). This function computes the p-value for each of the null values specified in the parameter rho.zero.

pvals.ICC2r.nointer(dfra, rho.zero = 0)

Arguments

• dfra: This is a data frame containing 3 columns or more. The first column contains subject numbers (there could be duplicates if a subject was assigned multiple ratings) and each of the remaining columns is associated with a particular rater and contains its numeric ratings.
• rho.zero: This is an optional parameter that represents a vector containing an arbitrary number of null values between 0 and 1 for which a p-value will be calculated. If not specified then its default value will be 0.

Returns

This function returns a vector containing p-values associated with the null values specified in the parameter rho.zero.

Examples

#iccdata1 is a small dataset that comes with the package. Use it as follows:
library(irrICC)
iccdata1 #see what the iccdata1 dataset looks like
pvals.ICC2r.nointer(iccdata1)
pvals.ICC2r.nointer(iccdata1,seq(0.2,0.5,0.05))

References

Gwet, K.L. (2014): Handbook of Inter-Rater Reliability - 4th ed. chapter 9, section 9.5.1, equation 9.5.15, Advanced Analytics, LLC.