ttest.ac2: Paired t-test for the difference of 2 AC2 coefficients.

In kgwet/pairedCAC: Testing the difference of correlated agreement coefficients for statistical significance

Description

The ttest.ac2 function performs the paired t-test for testing the difference between two correlated Gwet's AC_2 coefficients for statistical significance. It implements the linearization method of Gwet (2016).

Usage

ttest.ac2(
  g1.ratings,
  g2.ratings,
  weights = "unweighted",
  conflev = 0.95,
  N = Inf
)

Arguments

g1.ratings	is a mandatory parameter representing the first data frame of ratings.
g2.ratings	is a mandatory parameter representing the second data frame of ratings.
weights	is an optional parameter that defines the weights needed in a weighted analysis. It's default value is “unweighted” which requests the unweighted analysis.
conflev,	is an optional parameter representing the confidence level. It's default value is 0.95.
N	is an optional parameter representing the size of the subject population. It's default value is infinity.

Details

The 2 required parameters "g1.ratings" and "g2.ratings", which are the 2 groups of raters being compared, must have the exact same number of rows, and each column represents one rater and contains its ratings (numeric or alphabetic). All subjects that are not rated by any rater must be excluded from the dataset.

References

Gwet, K. L. (2008). Computing inter-rater reliability and its variance in the presence of high agreement. British Journal of Mathematical and Statistical Psychology, 61, 29-48.

Gwet, K. L. (2016). Testing the Difference of Correlated Agreement Coefficients for Statistical Significance, Educational and Psychological Measurement, Vol 76(4) 609-637.

kgwet/pairedCAC documentation built on Dec. 21, 2021, 6:37 a.m.