krippen_2_raw: Krippendorff's Alpha

In emilelatour/lagree: Calculate various interrater agreement coefficients

Krippendorff's Alpha

Description

Krippendorff's Alpha and its standard error for 2 raters when input dataset is a contingency table

Usage

krippen_2_table(
  table,
  weights = "unweighted",
  conf_lev = 0.95,
  N = Inf,
  test_value = 0,
  alternative = "two.sided"
)

Arguments

table	A qxq matrix (or contingency table) showing the distribution of subjects by rater, where q is the number of categories. This is the only argument you must specify if you want the unweighted analysis
weights	One of the following to calculate weight based on defined methods: "unweighted", "quadratic", "linear", "ordinal", "radical", "ratio", "circular", "bipolar". The default is "unweighted", a diagonal matrix where all diagonal numbers equal to 1, and all off-diagonal numbers equal to 0. This special weight matrix leads to the unweighted analysis. You may specify your own q x q weight matrix here
conf_lev	The confidence level associated with the agreement coefficient's confidence interval. Default is 0.95.
N	An optional parameter representing the total number of subjects in the target subject population. Its default value is infinity, which for all practical purposes assumes the target subject population to be very large and will not require any finite-population correction when computing the standard error.
test_value	value to test the estimated AC against. Default is 0.
alternative	a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".

Value

A tbl_df with the coefficient, standard error, lower and upper confidence limits.

References

Gwet, K. (2014). Handbook of Inter-Rater Reliability: The Definitive Guide to Measuring the Extent of Agreement Among Multiple Raters, 4th Edition. Advanced Analytics, LLC;

Krippendorff (1970). "Bivariate agreement coefficients for reliability of data." Sociological Methodology,2,139-150

Krippendorff (1980). Content analysis: An introduction to its methodology (2nd ed.), New-bury Park, CA: Sage.

Examples

ratings <- matrix(c(5, 3, 0, 0,
                    3, 11, 4, 0,
                    2, 13, 3, 4,
                    1, 2, 4, 14), ncol = 4, byrow = TRUE)

krippen_2_table(table = ratings)

krippen_2_table(table = ratings,
               weights = "quadratic")

krippen_2_table(table = ratings,
               weights = ac_weights(categ = c(1:4),
                                    weight_type = "quadratic"))

my_weights <- matrix(c(1.0000000, 0.8888889, 0.5555556, 0.0000000,
                       0.8888889, 1.0000000, 0.8888889, 0.5555556,
                       0.5555556, 0.8888889, 1.0000000, 0.8888889,
                       0.0000000, 0.5555556, 0.8888889, 1.0000000),
                     ncol = 4, byrow = TRUE)

krippen_2_table(table = ratings,
               weights = my_weights)

emilelatour/lagree documentation built on Sept. 18, 2024, 5:19 p.m.