kappaetc
The name is parsed "kappa, etc."
Stata’s built-in capabilities for assessing interrater agreement are
pretty much limited to two version of the kappa-statistic: Cohen’s
(weighted) kappa for two raters and Fleiss’ kappa (which is actually a
generalization of Scott’s Pi) for three or more raters. Despite the fact
that these statistics have been criticized for a long time and
alternatives have been developed, these measures appear to remain the
ones most often used. One reason seems to be the limited availability of
alternatives in statistical software.
kappaetc is intended to fill this gap in Stata. The program implements methods and formulas discussed in Gwet (2014). It calculates six agreement coefficients along with their standard errors and confidence intervals for any number of raters and any number of categories. It handles varying numbers of raters per subject and provides seven prerecorded weights, suitable for any level of measurement.
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kappaetc is intended to fill this gap in Stata. The program implements methods and formulas discussed in Gwet (2014). It calculates six agreement coefficients along with their standard errors and confidence intervals for any number of raters and any number of categories. It handles varying numbers of raters per subject and provides seven prerecorded weights, suitable for any level of measurement.
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. webuse rvary2
. kappaetc rater1-rater5
Interrater agreement Number of subjects = 10
Number of raters = 5
Ratings per subject: min = 3
avg = 4.7
max = 5
-------------------------------------------------------------------------------
| Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------+---------------------------------------------------------
Percent Agreement | 0.5833 0.0759 7.69 0.000 0.4117 0.7550
Brennan and Prediger | 0.3750 0.1138 3.29 0.009 0.1175 0.6325
Cohen/Conger's Kappa | 0.3853 0.1049 3.67 0.005 0.1481 0.6225
Fleiss' Kappa | 0.3586 0.1207 2.97 0.016 0.0856 0.6316
Gwet's AC | 0.3829 0.1145 3.34 0.009 0.1238 0.6420
Krippendorff's alpha | 0.3897 0.1462 2.66 0.026 0.0589 0.7205
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