Full Economic Evaluation
Full economic evaluation is a study design that compares the costs and health outcomes of two or more healthcare options to judge value for money.
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.
Fully Incremental Analysis
Fully incremental analysis compares three or more mutually exclusive health care options, each with the next cheaper option not ruled out by dominance.
Game Theory
Game theory in health economics analyses strategic choices by payers, providers, manufacturers and patients whose outcomes depend on what the others do.
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.
Generalized Cost-Effectiveness
Generalized cost-effectiveness analysis (GCEA) is a WHO method that compares health interventions, alone and combined, with a null where none is provided.
Generalized Estimating Equations
Generalized estimating equations (GEE) are a regression method for population-averaged effects from repeated or clustered data, such as trial utilities.
Generalized Gamma Model
The generalised gamma model is a three-parameter survival model used in health economics to extrapolate trial data, nesting the Weibull and log-normal.
Generalized Linear Model
A generalised linear model (GLM) relates an outcome's mean to covariates via a link function, used in health economics for skewed costs and counts.
Genetic Algorithm
A genetic algorithm is a search method based on natural selection that evolves candidate solutions, used to calibrate and optimise health economic models.
Gibbs Sampling
Gibbs sampling is a Markov chain Monte Carlo method that fits Bayesian models, such as meta-analyses, by drawing each parameter in turn given the others.
Gini Coefficient Health
The health Gini coefficient is a 0 to 1 index of how unequally a health outcome, such as length of life, is spread among people ranked by their own health.
Global Sensitivity Analysis
Global sensitivity analysis (GSA) measures how much each uncertain input of a health economic model drives variation in results as all inputs vary at once.
Gompertz Distribution
A probability distribution characterised by a hazard rate rising exponentially with time, originally developed to describe human mortality increasing with age.
Gompertz Model
A survival model based on the Gompertz distribution, assuming the hazard rate rises exponentially over time, a pattern common in age-related mortality.
Goodness of Fit
Goodness of fit describes how adequately a statistical model or probability distribution represents the observed data for its intended purpose.
Goodness of Fit Test
A goodness of fit test assesses whether a specified discrepancy between observed data and a proposed probability model is unusually large under that model’s sampling assumptions.
Gradient Descent
Gradient descent is an iterative first-order optimization method that reduces a differentiable objective function by repeatedly moving the parameter vector in the direction opposite its gradient.