A Latent Trait Finite Mixture Model for the Analysis of Rating Agreement

This article presents a latent distribution model for the analysis of agreement on dichotomous or ordered category ratings. The model includes parameters that characterize bias, category definitions, and measurement error for each rater or test. Parameter estimates can be used to evaluate rater perf...

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Bibliographic Details
Published in:Biometrics 1993-09, Vol.49 (3), p.823-835
Main Authors: Uebersax, John S., Grove, William M.
Format: Article
Language:English
Subjects:
Biological and medical sciences
Biometrics
Data Interpretation, Statistical
Data models
Estimate reliability
Fundamental and applied biological sciences. Psychology
Gaussian distributions
Humans
Liver Neoplasms - diagnosis
Liver Neoplasms - secondary
Maximum likelihood estimation
Modeling
Models, Statistical
Observer Variation
Parametric models
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Psychometrics. Statistics. Methodology
Reproducibility of Results
Standard error
Statistical results
Statistics
Statistics. Mathematics
Tuberculosis - diagnosis
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Description
Summary:This article presents a latent distribution model for the analysis of agreement on dichotomous or ordered category ratings. The model includes parameters that characterize bias, category definitions, and measurement error for each rater or test. Parameter estimates can be used to evaluate rater performance and to improve classification or measurement with use of multiple ratings. A simple maximum likelihood estimation procedure is described. Two examples illustrate the approach. Although considered in the context of analyzing rater agreement, the model provides a general approach for mixture analysis using two or more ordered-category measures.
ISSN:0006-341X
1541-0420
DOI:10.2307/2532202