Testing the equality of two dependent kappa statistics
โ Scribed by Allan Donner; Mohamed M. Shoukri; Neil Klar; Emma Bartfay
- Publisher
- John Wiley and Sons
- Year
- 2000
- Tongue
- English
- Weight
- 116 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0277-6715
No coin nor oath required. For personal study only.
โฆ Synopsis
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-"t procedure that takes into account the dependency between samples is recommended.
๐ SIMILAR VOLUMES
With measurements taken on subjects over time, on matched pairs of subjects or on clusters of subjects, the data often contain pairs of correlated dichotomous responses. McNemar's test is perhaps the best known test to compare two correlated binomial proportions. The salient feature of McNemar's tes