Three-group ROC predictive analysis for ordinal outcomes
نویسندگان
چکیده
منابع مشابه
Three-group ROC analysis: A nonparametric predictive approach
Measuring the accuracy of diagnostic tests is crucial in many application areas, in particular medicine and health care. The receiver operating characteristic (ROC) surface is a useful tool to assess the ability of a diagnostic test to discriminate among three ordered classes or groups. In this paper, nonparametric predictive inference (NPI) for three-group ROC analysis is presented. NPI is a f...
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Nowadays the area under the receiver operating characteristics (ROC) curve, which corresponds to the Wilcoxon–Mann–Whitney test statistic, is increasingly used as a performance measure for binary classification systems. In this article we present a natural generalization of this concept for more than two ordered categories, a setting known as ordinal regression. Our extension of the Wilcoxon–Ma...
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Ordinal regression learning has characteristics of both multi-class classification and metric regression because labels take ordered, discrete values. In applications of ordinal regression, the misclassification cost among the classes often differs and with different misclassification costs the common performance measures are not appropriate. Therefore we extend ROC analysis principles to ordin...
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Diagnostic tests commonly are characterized by their true positive (sensitivity) and true negative (specificity) classification rates, which rely on a single decision threshold to classify a test result as positive. A more complete description of test accuracy is given by the receiver operating characteristic (ROC) curve, a graph of the false positive and true positive rates obtained as the dec...
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Nonparametric predictive inference (NPI) is a powerful frequentist statistical framework based only on an exchangeability assumption for future and past observations, made possible by the use of lower and upper probabilities. In this paper, NPI is presented for ordinal data, which are categorical data with an ordering of the categories. The method uses a latent variable representation of the ob...
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ژورنال
عنوان ژورنال: Communications in Statistics - Theory and Methods
سال: 2016
ISSN: 0361-0926,1532-415X
DOI: 10.1080/03610926.2016.1212074