Expected Value
Expected value is the probability-weighted mean of an uncertain outcome, such as a cost or QALY total, across all its possible values.
Encyclopaedia
Explore comprehensive, evidence-informed explanations of key health economics concepts, including their development, application and relationships to other concepts. Published entries are validated through human expert review.
Concepts, entries and ontology terms
A concept page is a published entry on the wiki. Some concepts also have a full encyclopaedia article. The Health Economics Ontology (HEO) holds every concept, including dictionary terms without an article, so it is larger than the list of published pages. The knowledge graph shows how concepts relate to each other.
Expected Value Analysis
Expected value analysis compares health care options under uncertainty by their probability-weighted average outcomes, such as expected costs and QALYs.
Expected Value of Partial Perfect Information
Expected value of partial perfect information (EVPPI) is the expected gain in net benefit from knowing selected model parameters exactly before deciding.
Expected Value of Perfect Information
Expected value of perfect information (EVPI) is the expected gain from removing all uncertainty in a funding decision, the upper limit on research value.
Expected Value of Sample Information
Expected value of sample information (EVSI) is the expected net benefit gained by deciding after a specific proposed study reports instead of deciding now.
Exponential Distribution
A probability distribution characterised by a constant hazard rate over time, used to model event timing when risk is assumed not to change.
Exponential Model
A survival model assuming time-to-event data follow an exponential distribution, implying a constant hazard rate throughout the modelled time horizon.
Extrapolation
Extrapolation is the projection of survival, treatment effects or costs beyond trial follow-up so an economic model can estimate lifetime outcomes.
First-Order Index
A first-order index in variance-based sensitivity analysis is the fraction of model-output variance explained by changes in the conditional mean when one uncertain input varies on its own under the specified input distribution.
Fleming-Harrington Estimator
The Fleming-Harrington estimator derives survival from censored trial data as the exponential of minus a cumulative hazard corrected for tied event times.
Fleming-Harrington Test
The Fleming-Harrington test is a weighted log-rank test whose two parameters tilt survival comparisons in trials and HTA towards early or late differences.
Flexible Parametric Model
A flexible parametric model is a survival model that uses splines in time to fit complex hazard shapes, giving smooth curves for extrapolation in HTA.
Folding Back
Folding back is the backward evaluation of a decision tree that takes probability-weighted values at chance nodes and selects the preferred feasible action at decision nodes under a stated objective.
Force of Infection
The force of infection is the rate at which a susceptible person acquires infection, the hazard driving dynamic models of vaccines and infection control.
Fractional Polynomial
A fractional polynomial is a regression function using one or two powers of a variable such as age or time to model curved effects on risk or survival.
Frailty Model
A frailty model is a survival model in which an unobserved random effect multiplies each patient's hazard to capture risk differences that covariates miss.
Gamma Distribution
The gamma distribution is a continuous probability distribution on positive values, defined here by shape and scale parameters that control its mean, variance, and skew.
Gaussian Process
A Gaussian process is a probability distribution over unknown functions, used in health economics to emulate slow decision models and to estimate EVPPI.
Gaussian Process Regression
Gaussian process regression is a probabilistic method that predicts an unknown function from observed input-output pairs by conditioning a joint Gaussian model specified through a mean and covariance function.
Gaussian Quadrature
Gaussian quadrature is a family of numerical integration methods that approximates a definite integral using carefully chosen evaluation points and weights.