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A high ROC AUC, such as 0.9 for example, might correspond to low values of precision and negative predictive value, such as 0.2 and 0.1 in the [0, 1] range. If one performed a binary classification, obtained an ROC AUC of 0.9 and decided to focus only on this metric, they might overoptimistically believe their binary test was excellent.
For example, gentamicin is an antibiotic that can be nephrotoxic (kidney damaging) and ototoxic (hearing damaging); measurement of gentamicin through concentrations in a patient's plasma and calculation of the AUC is used to guide the dosage of this drug. [3] AUC becomes useful for knowing the average concentration over a time interval, AUC/t.
Phi measures how better (or worse) is a classification, with respect to the random classification, which is characterized by Phi = 0. According to the reference values suggested by Cohen, [8] one can take Phi = 0.35 as a minimum acceptable level of Phi for a classification. In the ROC space, Phi equal to a non null constant corresponds to the ...
When measuring diagnostic ability, a commonly reported measure is the area under the curve (AUC). The AUC is calculable from the TOC and the ROC. The value of the AUC is consistent for the same data whether you are calculating the area under the curve for a TOC curve or a ROC curve.
The absolute bioavailability is the dose-corrected area under curve (AUC) non-intravenous divided by AUC intravenous. The formula for calculating the absolute bioavailability, F, of a drug administered orally (po) is given below (where D is dose administered).
In economics, the Gini coefficient (/ ˈ dʒ iː n i / JEE-nee), also known as the Gini index or Gini ratio, is a measure of statistical dispersion intended to represent the income inequality, the wealth inequality, or the consumption inequality [2] within a nation or a social group.
The price elasticity of supply (PES or E s) is commonly known as “a measure used in economics to show the responsiveness, or elasticity, of the quantity supplied of a good or service to a change in its price.” Price elasticity of supply, in application, is the percentage change of the quantity supplied resulting from a 1% change in price.
Free add-on to STATA to compute inequality and poverty measures; Free Online Software (Calculator) computes the Gini Coefficient, plots the Lorenz curve, and computes many other measures of concentration for any dataset; Free Calculator: Online and downloadable scripts (Python and Lua) for Atkinson, Gini, and Hoover inequalities