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Quantile-based Nonparametric Test for Comparing Two Diagnostic Tests
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 Title & Authors
Quantile-based Nonparametric Test for Comparing Two Diagnostic Tests
Kim, Young-Min; Song, Hae-Hiang;
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 Abstract
Diagnostic test results, which are approximately normal with a few number of outliers, but non-normal probability distribution, are frequently observed in practice. In the evaluation of two diagnostic tests, Greenhouse and Mantel (1950) proposed a parametric test under the assumption of normality but this test is inappropriate for the above non-normal case. In this paper, we propose a computationally simple nonparametric test that is based on quantile estimators of mean and standard deviation, instead of the moment-based mean and standard deviation as in some parametric tests. Parametric and nonparametric tests are compared with simulations under the assumption of, respectively, normality and non-normality, and under various combinations of the probability distributions for the normal and diseased groups.
 Keywords
Diagnostic tests;nonparametric test;quantile estimator;
 Language
Korean
 Cited by
 References
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