2002
DOI: 10.1002/sim.1011
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A non‐parametric method for the comparison of partial areas under ROC curves and its application to large health care data sets

Abstract: The receiver operating characteristic (ROC) curve is a statistical tool for evaluating the accuracy of diagnostic tests. Investigators often compare the validity of two tests based on the estimated areas under the respective ROC curves. However, the traditional way of comparing entire areas under two ROC curves is not sensitive when two ROC curves cross each other. Also, there are some cutpoints on the ROC curves that are not considered in practice because their corresponding sensitivities or specificities are… Show more

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Cited by 117 publications
(61 citation statements)
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“…Univariate and multivariate statistical analyses were performed to determine the significance of various factors using the Kaplan-Meier method and log-rank test [16]. P -values < 0.05 were considered statistically significant.…”
Section: Methodsmentioning
confidence: 99%
“…Univariate and multivariate statistical analyses were performed to determine the significance of various factors using the Kaplan-Meier method and log-rank test [16]. P -values < 0.05 were considered statistically significant.…”
Section: Methodsmentioning
confidence: 99%
“…Cancer-related mortality was calculated, and the follow-up period was determined from the date of diagnosis to the date of cancer-related mortality of the last survivor undergoing follow-up care. Survival rates were calculated using the Kaplan-Meier method and compared using a log-rank test [12]. A multivariate Cox proportional hazard regression model was used to estimate the mortality risk.…”
Section: Methodsmentioning
confidence: 99%
“…All of the data were expressed as means ± standard error of the mean. A univariate statistical analysis was performed to determine the significance of various factors using the Kaplan-Meier method and a logrank test [14]. p < 0.05 was considered statistically significant.…”
Section: Methodsmentioning
confidence: 99%