Receiver Operating Characteristic (ROC) Curve for Medical Researchers.

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dc.contributor.authorKumar, Rajeev
dc.contributor.authorIndrayan, Abhaya
dc.date.accessioned2015-12-22T08:18:30Z
dc.date.available2015-12-22T08:18:30Z
dc.date.issued2011-04
dc.description.abstractSensitivity and specificity are two components that measure the inherent validity of a diagnostic test for dichotomous outcomes against a gold standard. Receiver operating characteristic (ROC) curve is the plot that depicts the trade-off between the sensitivity and (1-specificity) across a series of cut-off points when the diagnostic test is continuous or on ordinal scale (minimum 5 categories). This is an effective method for assessing the performance of a diagnostic test. The aim of this article is to provide basic conceptual framework and interpretation of ROC analysis to help medical researchers to use it effectively. ROC curve and its important components like area under the curve, sensitivity at specified specificity and vice versa, and partial area under the curve are discussed. Various other issues such as choice between parametric and non-parametric methods, biases that affect the performance of a diagnostic test, sample size for estimating the sensitivity, specificity, and area under ROC curve, and details of commonly used softwares in ROC analysis are also presented.en_US
dc.identifier.citationKumar Rajeev, Indrayan Abhaya. Receiver Operating Characteristic (ROC) Curve for Medical Researchers. Indian Pediatrics. 2011 Apr; 48(4): 277-287.en_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/168808
dc.language.isoenen_US
dc.source.urihttps://www.indianpediatrics.net/apr2011/apr-277-287.htmen_US
dc.subjectSensitivityen_US
dc.subjectSpecificityen_US
dc.subjectReceiver operating characteristic curveen_US
dc.subjectSample sizeen_US
dc.subjectOptimal cut-off pointen_US
dc.subjectPartial area under the curveen_US
dc.titleReceiver Operating Characteristic (ROC) Curve for Medical Researchers.en_US
dc.typeArticleen_US
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