kappa_test {kappaGold} | R Documentation |
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")