Log‐linear modelling of pairwise interobserver agreement on a categorical scale
作者:
Mark P. Becker,
Alan Agresti,
期刊:
Statistics in Medicine
(WILEY Available online 1992)
卷期:
Volume 11,
issue 1
页码: 101-114
ISSN:0277-6715
年代: 1992
DOI:10.1002/sim.4780110109
出版商: Wiley Subscription Services, Inc., A Wiley Company
数据来源: WILEY
摘要:
AbstractThis article uses log‐linear models to describe pairwise agreement among several raters who classify a sample on a subjective categorical scale. The models describe agreement structure simultaneously for second‐order marginal tables of a multidimensional cross‐classification of ratings. Practical difficulties arise in fitting the models, because models refer to pairwise marginal tables of a very large and sparse table. A standard analysis that treats the marginal tables as independent yields consistent estimates of model parameters, but not of the covariance matrix of the estimates. We estimate the covariance matrix using the jackknife. We apply the models to describe agreement between evaluations made by seven pathologists of carcinomain situof the uterine cervix, using a five‐level ordinal scale. Previous analyses showed differences among the pathologists in their pairwise levels of agreement, but we observe near homogeneity in the dependence structure of their
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