title: Modelling patterns of agreement and disagreement.
abstract: This article presents a survey of ways of statistically modelling patterns of observer agreement and disagreement. Main emphasis is placed on modelling inter-observer agreement for categorical responses, both for nominal and ordinal response scales. Models discussed include (1) simple cell-probability models based on Cohen's kappa that focus on beyond-chance agreement, (2) loglinear models for square tables, such as quasi-independence and quasi-symmetry models, (3) latent class models that express the joint distribution between ratings as a mixture of clusters for homogeneous subjects, each cluster having the same 'true' rating, and 4) Rasch models, which decompose subject-by-observer rating distributions using observer and subject main effects. Models can address two distinct components of agreement--strength of association between ratings, and similarity of marginal distributions of the ratings.
authors.affiliation: Department of Statistics, University of Florida, Gainesville 32611.
authors.forename: A
authors.initials: A
authors.lastname: Agresti
mesh_terms: D016014:Linear Models; D015233:Models, Statistical; D015588:Observer Variation; D011336:Probability