1985
DOI: 10.1016/0038-0121(85)90007-2
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Mathematical partitioning of the receiver operating curve: A diagnostic tool for medical decision making

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Cited by 7 publications
(7 citation statements)
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“…A larger area under the ROC curve represents more reliability and good discrimination of the scoring system. Differences between the AUC values of all predictive tests were calculated, and a P value of 0.05 was defined as statistically significant amongst predictors [21] Differences between the AUC values of six predictor tests were analyzed using MedCalc statistical software 9.3.6.0. The data were analyzed using SPSS version 20 (SPSS, Chicago, IL).…”
Section: Methodsmentioning
confidence: 99%
“…A larger area under the ROC curve represents more reliability and good discrimination of the scoring system. Differences between the AUC values of all predictive tests were calculated, and a P value of 0.05 was defined as statistically significant amongst predictors [21] Differences between the AUC values of six predictor tests were analyzed using MedCalc statistical software 9.3.6.0. The data were analyzed using SPSS version 20 (SPSS, Chicago, IL).…”
Section: Methodsmentioning
confidence: 99%
“…A value of 0.5 under the ROC curve indicated that the variable performs no better than chance and a value of 1.0 indicates perfect discrimination. A larger area under the ROC curve represents more reliability[ 31 32 ] and good discrimination of the scoring system. Differences between the AUC values of all predictive tests were calculated, and a P value of 0.05 was defined as statistically significant.…”
Section: Methodsmentioning
confidence: 99%
“…A larger area under the ROC curve denotes more reliability[21] and good discrimination of the scoring system. Additionally, the ROC curves were used to recognize the optimal predictive cutoff points for each test.…”
Section: Methodsmentioning
confidence: 99%
“…A value of 0.5 under the ROC curve indicates that the variable performs no better than chance and a value of 1.0 implies perfect discrimination. A larger area under the ROC curve denotes more reliability[ 21 ] and good discrimination of the scoring system. Additionally, the ROC curves were used to recognize the optimal predictive cutoff points for each test.…”
Section: Methodsmentioning
confidence: 99%