kappa_test: Significance test for homogeneity of kappa coefficients in...

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

Significance test for homogeneity of kappa coefficients in independent groups

Description

The null hypothesis states that the kappas for all involved groups are the same ("homogeneous"). A prerequisite is that the groups are independent of each other, this means the groups are comprised of different subjects and each group has different raters. Each rater employs a nominal scale. The test requires estimates of kappa and its standard error per group.

Usage

kappa_test(kappas, val = "value0", se = "se0", conf.level = 0.95)

Arguments

kappas	list of kappas from different groups. It uses the kappa estimate and its standard error.
val	character. Name of field to extract kappa coefficient estimate.
se	character. Name of field to extract standard error of kappa.
conf.level	numeric. confidence level of confidence interval for overall kappa

Details

A common overall kappa coefficient across groups is estimated. The test statistic assesses the weighted squared deviance of the individual kappas from the overall kappa estimate. The weights depend on the provided standard errors. Under H0, the test statistics is chi-square distributed.

Value

list containing the test results, including the entries statistic and p.value (class htest)

References

Joseph L. Fleiss, Statistical Methods for Rates and Proportions, 3rd ed., 2003, section 18.1

Examples

# three independent agreement studies (different raters, different subjects)
# each study involves two raters that employ a binary rating scale
k2_studies <- lapply(agreem_binary, kappa2)

# combined estimate and test for homogeneity of kappa
kappa_test(kappas = k2_studies, val = "value", se = "se")

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