kappa_test_corr: Test for homogeneity of kappa in correlated groups

In kappaGold: Agreement of Nominal Scale Raters (with a Gold Standard)

Test for homogeneity of kappa in correlated groups

Description

Bootstrap test on kappa based on data with common subjects. The differences in kappa between all groups (but first) relative to first group (e.g., Group 2 - Group 1) are considered.

Usage

kappa_test_corr(
  ratings,
  grpIdx,
  kappaF,
  kappaF_args = list(),
  B = 100,
  alternative = "two.sided",
  conf.level = 0.95
)

Arguments

ratings	matrix. ratings as sbj x raters, including the multiple groups to be tested
grpIdx	list. Comprises numeric index vectors per group. Each group is defined as set of raters (i.e., columns)
kappaF	function or list of functions. kappa function to apply on each group.
kappaF_args	list. Further arguments for the kappa function. By default, these settings apply to all groups, but the settings can be specified per group (as list of lists).
B	numeric. number of bootstrap samples. At least 1000 are recommended for stable results.
alternative	character. Direction of alternative. Currently only 'two.sided' is supported.
conf.level	numeric. confidence level for confidence intervals

Value

list. test results as class htest. The confidence interval shown by print refers to the 1st difference k1-k2.

Note

Due to limitations of the htest print method the confidence interval shown by print refers to the 1st difference k1-k2. If there are more than 2 groups access all confidence intervals via entry conf.int.

Examples

# Compare Fleiss kappa between students and expert raters
# For real analyses use more bootstrap samples (B >= 1000)
kappa_test_corr(ratings = SC_test, grpIdx = list(S=1:39, E=40:50), B = 125,
                kappaF = kappam_fleiss,
                kappaF_args = list(variant = "fleiss", ratingScale=-2:2))

kappaGold documentation built on April 4, 2025, 1:02 a.m.