Asymptotic distributions of kappa statistics and their differences with many raters, many rating categories and two conditions
| Autor: | Enrico Bibbona, Mauro Gasparini, Marco Daperno, Guido Pagana, Luca Grassano |
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| Rok vydání: | 2017 |
| Předmět: |
Statistics and Probability
Biometry agreement correlated kappa statistics de Finetti representation theorem inflammatory bowel diseases Statistics Probability and Uncertainty Asymptotic distribution 050109 social psychology 01 natural sciences 010104 statistics & probability Cohen's kappa Statistics Econometrics 0501 psychology and cognitive sciences 0101 mathematics Categorical variable Reliability (statistics) Mathematics Models Statistical 05 social sciences Probability and statistics General Medicine Confidence interval Delta method Sample size determination Sample Size Probability and Uncertainty Monte Carlo Method |
| Zdroj: | Biometrical journal. Biometrische Zeitschrift. 60(1) |
| ISSN: | 1521-4036 |
| Popis: | In clinical research and in more general classification problems, a frequent concern is the reliability of a rating system. In the absence of a gold standard, agreement may be considered as an indication of reliability. When dealing with categorical data, the well-known kappa statistic is often used to measure agreement. The aim of this paper is to obtain a theoretical result about the asymptotic distribution of the kappa statistic with multiple items, multiple raters, multiple conditions, and multiple rating categories (more than two), based on recent work. The result settles a long lasting quest for the asymptotic variance of the kappa statistic in this situation and allows for the construction of asymptotic confidence intervals. A recent application to clinical endoscopy and to the diagnosis of inflammatory bowel diseases (IBDs) is shortly presented to complement the theoretical perspective. |
| Databáze: | OpenAIRE |
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