On modelling agreement and category distinguishability on an ordinal scale

Lianyan Fu, Wei Gao*, Man Lai TANG, Ning Zhong Shi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)4413-4426
Number of pages14
JournalCommunications in Statistics - Theory and Methods
Volume41
Issue number24
DOIs
Publication statusPublished - Nov 2012

Scopus Subject Areas

  • Statistics and Probability

User-Defined Keywords

  • Category distinguishability
  • Diagonal-parameter symmetry model
  • Log-linear models
  • Ordinal categories

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