Receiver Operating Characteristic (ROC) Curve for Medical Researchers.
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Date
2011-04
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Abstract
Sensitivity 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.
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Keywords
Sensitivity, Specificity, Receiver operating characteristic curve, Sample size, Optimal cut-off point, Partial area under the curve
Citation
Kumar Rajeev, Indrayan Abhaya. Receiver Operating Characteristic (ROC) Curve for Medical Researchers. Indian Pediatrics. 2011 Apr; 48(4): 277-287.