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zbMATH Open
Article . 1986
Data sources: zbMATH Open
Biometrics
Article . 1986 . Peer-reviewed
Data sources: Crossref
Biometrics
Article . 1987
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The Kappa Coefficient of Agreement for Multiple Observers When the Number of Subjects is Small

The kappa coefficient of agreement for multiple observers when the number of subjects is small
Authors: Gross, Shulamith T.;

The Kappa Coefficient of Agreement for Multiple Observers When the Number of Subjects is Small

Abstract

Published results on the use of the kappa coefficient of agreement have traditionally been concerned with situations where a large number of subjects is classified by a small group of raters. The coefficient is then used to assess the degree of agreement among the raters through hypothesis testing or confidence intervals. A modified kappa coefficient of agreement for multiple categories is proposed and a parameter-free distribution for testing null agreement is provided, for use when the number of raters is large relative to the number of categories and subjects. The large-sample distribution of kappa is shown to be normal in the nonnull case, and confidence intervals for kappa are provided. The results are extended to allow for an unequal number of raters per subject.

Keywords

Biometry, Asymptotic distribution theory in statistics, Mood Disorders, large-sample distribution, Nonparametric tolerance and confidence regions, Diagnosis, multiple categories, Humans, unbalanced design, modified kappa coefficient of agreement, parameter-free distribution for testing null agreement, confidence intervals, Applications of statistics to psychology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
68
Top 10%
Top 1%
Average
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