Kappa Statistic
Kappa Statistic is a statistical measure of inter-rater agreement for categorical items that adjusts observed agreement for chance concordance, distinguishing it from simple percent agreement by quantifying the degree of agreement above what would be expected by random chance.
7.2K
Publications
589.8K
Citations
36.6K
Authors
7.1K
Institutions
Publications per year
2017–2026
2K
Variants
Cohen's Kappa Statistic
7.2K
The Measurement of Observer Agreement for Categorical Data
J. Richard Landis, Gary G. Koch · Biometrics · 1977 · 78.9K citations · Full text
Interrater reliability: the kappa statistic
Marry L. McHugh · Biochemia Medica · 2012 · 18.6K citations · Full text
Design and validation of a histological scoring system for nonalcoholic fatty liver disease†
David E. Kleiner, Elizabeth M. Brunt, Mark L. Van Natta et al. · Hepatology · 2005 · 10.7K citations
Interrater reliability: the kappa statistic.
Mary L. McHugh · PubMed · 2012 · 9.2K citations · Full text
1–5 of 7.2K
36.6K
19
h-index
19
h-index
12
h-index
10
h-index
10
h-index
1–5 of 36.6K
7.1K
University College London
London, United Kingdom
45 h-index
266 publications
16.7K citations

University of Toronto
Toronto, Canada
44 h-index
223 publications
11.2K citations

Johns Hopkins University
Baltimore, United States
41 h-index
260 publications
17.2K citations
Harvard University
Cambridge, United States
39 h-index
297 publications
24.9K citations
Universidade de São Paulo
São Paulo, Brazil
37 h-index
294 publications
11.9K citations
University of Washington
Seattle, United States
37 h-index
131 publications
12.3K citations

The University of Sydney
Sydney, Australia
35 h-index
163 publications
23.9K citations
Columbia University
New York, United States
34 h-index
130 publications
22.2K citations
1–8 of 7.1K
Repository · 380 publications · 32.6K citations
57
h-index
146 publications · 8.5K citations
49
h-index
AJR · 90 publications · 6.6K citations
46
h-index
56 publications · 5.2K citations
39
h-index
46 publications · 5.2K citations
32
h-index
1–5