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Reliability models for categorical data
Authors:Max R. Mickey  Claude O. Archer
Affiliation:1. Department of Biomathematics , University of California , Los Angeles, CA, 90024;2. Statistics Division , Internal Revenue Service , 1111 Constitution Avenue, Washington, D.C, 20024
Abstract:As assumed hypothetical consensus category corresponding to a case being classified provides a basis for assessment of reliability of judges. Equivalent judges are characterised by the joint probability distribution of the judge assignment and the consensus category. Estimates of the conditional probabilities of judge assignment given consensus category and of consensus category given judge assignments are indices of reliability. All parameters can be estimated if data include classifications of a number of cases by 3 or more judges. Restrictive assumptions are imposed to obtain models for data from classifications by two judges. Maximum likelihood estimation is discussed and illustrated by example for the 3 or more judges case.
Keywords:reliability  kappa  EM algorithm
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