On Modelling Agreement and Category Distinguishability on an Ordinal Scale

It is quite common that raters may need to classify a sample of subjects on a categorical scale. Perfect agreement can rarely be observed partly because of different perceptions about the meanings of the category labels between raters and partly because of factors such as intrarater variability. Usu...

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Bibliographic Details
Published in:Communications in statistics. Theory and methods 2012-12, Vol.41 (24), p.4413-4426
Main Authors: Fu, Lianyan, Gao, Wei, Tang, Man-Lai, Shi, Ning-Zhong
Format: Article
Language:English
Subjects:
Agreements
Category distinguishability
Diagonal-Parameter Symmetry Model
Exact sciences and technology
General topics
Log-linear models
Mathematics
Ordinal categories
Primary 62J12
Probability and statistics
Sciences and techniques of general use
Secondary 06A99
Statistics
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Summary:It is quite common that raters may need to classify a sample of subjects on a categorical scale. Perfect agreement can rarely be observed partly because of different perceptions about the meanings of the category labels between raters and partly because of factors such as intrarater variability. Usually, category indistinguishability occurs between adjacent categories. In this article, we propose a simple log-linear model combining ordinal scale information and category distinguishability between ordinal categories for modelling agreement between two raters. For the proposed model, no score assignment is required to the ordinal categories. An algorithm and statistical properties will be provided.
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2011.574216