Modeling agreement on categorical scales in the presence of random scorers

Abstract

Kappa coefficients are often used to assess agreement between two fixed scorers on categorical scales. Cohen's version is popular for nominal scales and the weighted version for ordinal scales. In the present paper, similar agreement coefficients are defined for random scorers. A partial-Bayesian methodology is then developed to directly relate these agreement coefficients to predictors through a multilevel model. Statistical properties of the proposed approach are studied using simulations. Finally, the approach is applied to gynecological and medical imaging data.