Exact Probability Distribution for the ROC Area under Curve
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Updated: Aug 5, 2025

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
Published on: October 27, 2023
Joakim Ekström1, Jim Åkerrén Ögren1, Tobias Sjöblom1
1Department of Immunology, Genetics, Pathology, Uppsala University, Rudbecklaboratoriet, 752 57 Uppsala, Sweden.
Abstract:
The Receiver Operating Characteristic (ROC) is a de facto standard for determining the accuracy of in vitro diagnostic (IVD) medical devices, and thus the exactness in its probability distribution is crucial toward accurate statistical inference. We show the exact probability distribution of the ROC AUC-value, hence exact critical values and p-values are readily obtained. Because the exact calculations are computationally intense, we demonstrate a method of geometric interpolation, which is exact in a special case but generally an approximation, vastly increasing computational speeds. The method is illustrated through open access data, demonstrating superiority of 26 composite biomarkers relative to a predicate device. Especially under correction for testing of multiple hypotheses, traditional asymptotic approximations are encumbered by considerable imprecision, adversely affecting IVD device development. The ability to obtain exact p-values will allow more efficient IVD device development.
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P-value
P-value stands for the probability value. P-value is the probability that, if the null hypothesis is true, the results from another randomly selected sample will be as extreme or more extreme as the results obtained from the given sample.
A large P-value calculated from the data indicates to not reject the null hypothesis. But a higher P-value does not mean that the null hypothesis is true. The smaller the P-value, the more...

