Testing the equality of two dependent kappa statistics

Stat Med. 2000 Feb 15;19(3):373-87. doi: 10.1002/(sici)1097-0258(20000215)19:3<373::aid-sim337>3.0.co;2-y.


Procedures are developed and compared for testing the equality of two dependent kappa statistics in the case of two raters and a dichotomous outcome variable. Such problems may arise when each of a sample of subjects are rated under two distinct settings, and it is of interest to compare the observed levels of inter-observer and intra-observer agreement. The procedures compared are extensions of previously developed procedures for comparing kappa statistics computed from independent samples. The results of a Monte Carlo simulation show that adjusting for the dependency between samples tends to be worthwhile only if the between-setting correlation is comparable in magnitude to the within-setting correlations. In this case, a goodness-of-fit procedure that takes into account the dependency between samples is recommended.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Analysis of Variance
  • Biometry / methods*
  • Humans
  • Models, Statistical
  • Observer Variation*