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Journal ArticleDOI

Large sample standard errors of kappa and weighted kappa.

TLDR
The statistics kappa and weighted kappa (Cohen, 1960) were introduced to provide coefficients of agreement between two raters for nominal scales as discussed by the authors, and they were used to provide a measure of the relative seriousness of the different possible disagreements.
Abstract
The statistics kappa (Cohen, 1960) and weighted kappa (Cohen, 1968) were introduced to provide coefficients of agreement between two raters for nominal scales. Kappa is appropriate when all disagreements may be considered equally serious, and weighted kappa is appropriate when the relative seriousness of the different possible disagreements can be specified. The papers describing these two statistics also present expressions for their standard errors. These expressions are incorrect, having been derived from the contradictory assumptions of fixed marginal totals and binomial variation of cell frequencies. Everitt (1968) derived the exact variances of weighted and unweighted kappa when the parameters are zero by assuming a generalized hypergeometric distribution. He found these expressions to be far too complicated for routine use, and offered, as alternatives, expressions derived by assuming binomial distributions. These alternative expressions are incorrect, essentially for the same reason as above. Assume that N subjects are distributed into k* cells by each of them being assigned to one of k categories by one rater and, independently, to one of the same k categories by a second

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The measurement of observer agreement for categorical data

TL;DR: A general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies is presented and tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interob server agreement are developed as generalized kappa-type statistics.
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The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability.

TL;DR: The use of kappa implicitly assumes that all disagreements are equally serious as discussed by the authors, which is not the case, and hence the use of the kappa scale implicitly implies that not all disagreements will be equally serious.
Journal ArticleDOI

Mixing patterns in networks.

TL;DR: This work proposes a number of measures of assortative mixing appropriate to the various mixing types, and applies them to a variety of real-world networks, showing that assortsative mixing is a pervasive phenomenon found in many networks.
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An application of hierarchical kappa-type statistics in the assessment of majority agreement among multiple observers.

TL;DR: A subset of 'observers who demonstrate a high level of interobserver agreement can be identified by using pairwise agreement statistics betweeni each observer and the internal majority standard opinion on each subject.
References
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Journal ArticleDOI

A Coefficient of agreement for nominal Scales

TL;DR: In this article, the authors present a procedure for having two or more judges independently categorize a sample of units and determine the degree, significance, and significance of the units. But they do not discuss the extent to which these judgments are reproducible, i.e., reliable.
Book

Linear statistical inference and its applications

TL;DR: Algebra of Vectors and Matrices, Probability Theory, Tools and Techniques, and Continuous Probability Models.
Journal ArticleDOI

Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit.

TL;DR: The Kw provides for the incorpation of ratio-scaled degrees of disagreement (or agreement) to each of the cells of the k * k table of joi.
Journal ArticleDOI

Linear Statistical Inference and its Applications

J. Aitchison, +1 more
- 01 Dec 1966 - 
TL;DR: Causal inference in statistics: An overview Linear Statistical Inference And Its Bayesian inference Wikipedia Springer Series in Statistics Stanford University Statistical Modeling, Causal Inference, and Social Science.
Journal ArticleDOI

Moments of the statistics kappa and weighted kappa

TL;DR: In this article, the mean and variance of the two statistics, kappa and weighted kappa, are used in measuring agreement between two raters, in the situation where they independently allocate a sample of subjects to a prearranged set of categories.