This article is an orphan, as no other articles link to it. Please introduce links to this page from related articles; try the Find link tool for suggestions. (March 2021)
Net benefit
Net benefit is calculated as a weighted combination of true and false positives, where is the threshold probability, true and false positives are count variables and N is the total number of observations.
Decision curve analysis evaluates a predictor for an event as a probability threshold is varied, typically by showing a graphical plot of net benefit against threshold probability. By convention, the default strategies of assuming that all or no observations are positive are also plotted.
Decision curve analysis is distinguished from other statistical methods like receiver operating characteristic (ROC) curves by the ability to assess the clinical value of a predictor. Applying decision curve analysis can determine whether using a predictor to make clinical decisions like performing biopsy will provide benefit over alternative decision criteria, given a specified threshold probability.
Threshold probability is defined as the minimum probability of an event at which a decision-maker would take a given action, for instance, the probability of cancer at which a doctor would order a biopsy. A lower threshold probability implies a greater concern about the event (e.g. a patient worried about cancer), while a higher threshold implies greater concern about the action to be taken (e.g. a patient averse to the biopsy procedure). Net benefit is a weighted combination of true and false positives, where the weight is derived from the threshold probability. The predictor could be a binary classifier, or a percentage risk from a prediction model, in which case a positive classification is defined by whether predicted probability is at least as great as the threshold probability.
and 24 Related for: Decision curve analysis information
A receiver operating characteristic curve, or ROC curve, is a graphical plot that illustrates the performance of a binary classifier model (can be used...
J.; Elkin, Elena B. (2006). "Decisioncurveanalysis: a novel method for evaluating prediction models". Medical Decision Making. 26 (6): 565–574. doi:10...
discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques...
Trouble with the Curve is a 2012 American sports drama film directed by Robert Lorenz and starring Clint Eastwood, Amy Adams, Justin Timberlake, Matthew...
Hozo, Iztok; Djulbegovic, Benjamin (December 2023). "Generalised decisioncurveanalysis for explicit comparison of treatment effects". Journal of Evaluation...
Laffer curve illustrates a theoretical relationship between rates of taxation and the resulting levels of the government's tax revenue. The Laffer curve assumes...
research. Survival analysis is used in several ways: To describe the survival times of members of a group Life tables Kaplan–Meier curves Survival function...
Decision trees are among the most popular machine learning algorithms given their intelligibility and simplicity. In decisionanalysis, a decision tree...
A learning curve is a graphical representation of the relationship between how proficient people are at a task and the amount of experience they have...
least profitable. By doing so it is possible to create a so-called 'Whale Curve', graphically showing the potential margin of an organisation. "Multidimensional...
implausible circumstances) of partial equilibrium analysis and the rationale for the upward slope of the supply curve in a market for a produced consumption good...
models can then be fed into a cost-benefit analysis program. A cumulative vehicle count curve, the N-curve, shows the cumulative number of vehicles that...
cumulative percentage column to the table, then plot the information Plot (#1) a curve with causes on x- and cumulative percentage on y-axis Plot (#2) a bar graph...
developed for use in fields such as survey analysis and neuroimaging. Mathematics portal Anscombe's quartet Curve fitting Estimation theory Forecasting Fraction...
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data...
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar...
topic is regression analysis, which focuses more on questions of statistical inference such as how much uncertainty is present in a curve that is fit to data...
products increases, shifting the demand curve higher at all possible prices. In addition, people's judgments and decisions are often influenced by systemic biases...
easily, and a more formal analysis posits up to five groups/curves over the period. However, modified forms of the Phillips curve that take inflationary...
fundamentals. Power companies may employ marginal abatement cost curves to guide their decisions about long-term capital investment strategies to select among...
Kam (2002). "A Data Complexity Analysis of Comparative Advantages of Decision Forest Constructors" (PDF). Pattern Analysis and Applications. 5 (2): 102–112...
In mathematics, a knee of a curve (or elbow of a curve) is a point where the curve visibly bends, specifically from high slope to low slope (flat or close...