Dictionary

The Dictionary provides concise definitions of health economics terms, arranged alphabetically for quick reference. Use it to understand unfamiliar terminology or confirm the meaning of a specific term.

1–50 of 54 terms matching “Uncertainty”

B

Beta DistributionBeta Probability Distribution, Beta Density: A flexible probability distribution bounded between zero and one, commonly used to represent uncertainty in probability parameters.
Bootstrap Standard ErrorBootstrapped SE, Resampled Standard Error: An estimate of a parameter's statistical uncertainty, calculated as the standard deviation of its value across many resampled datasets via bootstrapping.

C

Cost-Effectiveness AcceptabilityCE Acceptability, Acceptability Probability: The probability that an intervention offers good value for money at a given willingness-to-pay threshold, accounting for uncertainty in the cost and effect estimates.
Curative Model UncertaintyCure-Duration Uncertainty, Curative-Effect Uncertainty: The uncertainty surrounding a model's assumption about how long a one-time treatment's curative effect will last, given trial follow-up far shorter than the modelled lifetime.

D

Data VisualisationData Visualization, Information Graphics: In health economics and analytics, the graphical presentation of data to reveal patterns, relationships and uncertainty, such as plotting probabilistic sensitivity analysis results or quality-control trends.
Decision AnalysisDecision-Analytic Approach, Decision Modelling Framework: In health economics, a systematic quantitative approach to choosing among options under uncertainty by modelling their expected costs and consequences.
Decision UncertaintyDecision Risk, Probability of Wrong Decision: The probability that the currently preferred option in an evaluation is not actually the truly optimal choice, given uncertainty in the model's parameters.
Deliberative ProcessDeliberation, Reasoned Deliberation: A structured process of reasoned discussion of evidence and perspectives, used to reach well-justified decisions amid uncertainty or competing values.
Dirichlet DistributionDirichlet Prior, Multivariate Proportion Distribution: A multivariate distribution representing uncertainty in a set of proportions that must sum to one, such as transition probabilities from a state.

E

Emerging Infection EconomicsEmerging Pathogen Economics, Novel Infection Economics: The application of health economic evaluation to newly identified or newly significant infectious diseases, often marked by substantial scientific uncertainty.
Evidence GapResearch Gap, Missing-Evidence Area: An area of clinical or health economic uncertainty where insufficient or absent research evidence exists to confidently answer a relevant question.
Evidence SynthesisEvidence Combination, Research Synthesis: The structured integration and appraisal of findings from multiple studies to answer a defined question while accounting for comparability, bias and uncertainty.
Expected LossExpected Opportunity Loss, Probability-Weighted Loss: The probability-weighted average cost of making an incorrect decision under uncertainty, calculated across all possible states and their probabilities.
Expected Net BenefitAverage Net Benefit, ENB: Expected net benefit is the average net benefit of an alternative across the uncertainty represented in an economic evaluation, calculated at a stated cost-effectiveness threshold.
Expected UtilityEU, Utility Under Uncertainty: Expected utility is the probability-weighted average of the utilities assigned to an uncertain option's possible outcomes, used to rank choices under risk when preferences satisfy the required axioms.
Expected Value AnalysisExpected-Value Decision Making, Mean-Outcome Analysis: An approach to decision-making under uncertainty that evaluates options based on the probability-weighted average of their possible outcomes.
Expected Value of Partial Perfect InformationEVPPI, Partial Perfect-Information Value: The maximum value of completely resolving uncertainty in a specific subset of a model's parameters, while other parameters remain uncertain.
Expected Value of Perfect InformationEVPI, Perfect-Information Value: Expected value of perfect information is the expected increase in net benefit from eliminating all decision-relevant uncertainty before choosing among the available strategies.
Expected Value of Sample InformationEVSI, Sample-Information Value: Expected value of sample information is the expected increase in the value of a decision when a specified study’s possible data can update uncertainty before a strategy is chosen.

F

First-Order UncertaintyStochastic Uncertainty, Individual-Level Variability: Uncertainty arising from variation among individual patients within a modelled population, unlike parameter uncertainty concerning imperfect knowledge of a true average value.

G

Global Sensitivity AnalysisGSA, Simultaneous Sensitivity Analysis: Global sensitivity analysis, or GSA, evaluates how uncertainty in model inputs contributes to variation in model outputs when inputs vary across their full specified ranges or distributions.

H

Heterogeneity AnalysisSubgroup Variation Study, Effect Heterogeneity Study: An examination of how a model's results vary across different patient subgroups, unlike parameter uncertainty concerning imprecision in a single average population value.

I

ImprecisionEffect Estimate Uncertainty, Wide Confidence Interval: A GRADE evidence quality domain assessing whether a study's confidence intervals are narrow enough to support a confident conclusion about the true effect.
Inferential StatisticsStatistical Inference, Inferential Methods: A branch of statistics drawing conclusions about a broader population from sample data, incorporating formal methods for quantifying uncertainty.
Interval EstimateInterval Estimation, Range Estimate: A range of values, such as a confidence interval, calculated to convey the uncertainty surrounding a point estimate of a parameter.

J

Jackknife Standard ErrorJackknife SE, Jackknife Variance Estimate: An estimate of a parameter's statistical uncertainty calculated using the jackknife technique of omitting one observation at a time and examining resulting variability.

K

Kalman FilterState Estimator, Recursive State Filter: A recursive estimator that predicts an evolving latent state and updates that estimate and its uncertainty when a new noisy measurement arrives.

M

Markov Chain Monte CarloMCMC, Posterior Sampling: Markov chain Monte Carlo is a class of simulation methods that constructs a Markov chain with a chosen target distribution as its stationary distribution and uses dependent draws from the chain to approximate expectations and uncertainty under that distribution.
Methodological UncertaintyMethods Uncertainty, Analytic Uncertainty: Uncertainty arising from the choice of analytical methods or structural assumptions, such as discount rate, rather than the numerical values used within a fixed method.
Monte Carlo SimulationMCS, Second-Order Simulation: Monte Carlo simulation uses repeated random sampling to show how uncertainty in model inputs produces uncertainty in model outputs.
Multiple ImputationMI, Rubin's Rules: Multiple imputation is a missing-data method that creates several plausible completed datasets, analyses each for the same target, and pools the estimates and their uncertainty to reflect uncertainty about unobserved values.

N

Nested LoopTwo-Level Simulation, Nested Monte Carlo: A simulation structure in which one inner simulation runs repeatedly within each iteration of an outer simulation, used to separate sources of uncertainty.

O

Opportunity LossEOL, Loss from Wrong Decision: The difference in value between the outcome of the optimal decision and the outcome of the decision actually made under uncertainty.

P

Parameter DistributionInput Distribution, PSA Distribution: A parameter distribution is a probability model for the plausible values of an uncertain model input, specified from evidence and assumptions so its uncertainty can be propagated through an analysis.
Parameter ImportanceParameter Influence, Input Importance: A measure of how much a given input parameter contributes to the overall uncertainty in a model's results, used to prioritise further scrutiny.
Parameter UncertaintyInput Uncertainty, Sampling Uncertainty: Parameter uncertainty is uncertainty about the true values of quantities used as model inputs because those values are estimated from incomplete or imperfect evidence.
Precision AssessmentPrecision Appraisal, Imprecision Rating: An evaluation of an effect estimate's statistical precision, typically judged by the width of its confidence interval, wider meaning greater uncertainty.
Probabilistic Sensitivity AnalysisPSA, Probabilistic Analysis: Probabilistic sensitivity analysis (PSA) characterises parameter uncertainty by assigning probability distributions to uncertain model inputs and propagating joint samples through the model.
Probability of Cost-EffectivenessProbability CE, Likelihood of Cost-Effectiveness: The probability of cost-effectiveness is the model-based probability that an intervention meets a stated net-benefit criterion against specified alternatives at a given willingness-to-pay threshold under the assumed uncertainty distribution.

Q

Quality UncertaintyLemons Problem, Hidden-Quality Problem: A condition in which buyers cannot reliably judge a good's quality before purchase, risking markets dominated by lower-quality offerings.

R

ResamplingSample Reuse, Repeated Subsampling: A family of statistical methods that draw repeated samples from observed data to estimate uncertainty or validate models, including the bootstrap, jackknife and cross-validation.
Risk Sharing SchemeRisk Sharing Agreement, RSS, Outcomes-Based Scheme: An arrangement distributing the financial or clinical uncertainty of a new treatment's real-world performance between manufacturer and payer, often linked to outcomes.
Robust OptimisationRobust Optimization, Worst-Case Optimisation: An optimisation approach that selects a feasible decision to perform well under the worst parameter values in a specified uncertainty set, often requiring constraints to hold throughout that set.
Robust Standard ErrorRobust SE, Heteroskedasticity-Consistent Standard Error: An estimate of a regression coefficient's statistical uncertainty that remains valid even when standard modelling assumptions, such as constant error variance, are violated.

S

Second-Order UncertaintyDistributional Parameter Uncertainty, Hyperparameter Uncertainty: Uncertainty about the parameters of a probability distribution itself, such as its true mean and variance, distinct from the variability the distribution represents.
Stochastic ProgrammingOptimisation under Uncertainty, Recourse Programming: An optimisation framework incorporating parameter uncertainty directly into the process, seeking a solution that performs well across possible parameter values.
Structural UncertaintyModel-Structure Uncertainty, Structural Model Uncertainty: Uncertainty about the appropriate form, pathways, states or mechanisms of a model, including plausible alternative structures that can change its predictions or decisions.

U

UncertaintyImperfect Knowledge, Incomplete Information: A general term describing imperfect knowledge of the true values, structure, or methodological choices underlying a health economic model.
Uncertainty AssessmentUncertainty Evaluation, Uncertainty Appraisal: A systematic evaluation of how confident decision-makers should be in a model's results, given parameter, structural, and methodological uncertainty.
Uncertainty QuantificationUQ, Numerical Uncertainty Analysis: The formal process of measuring how much confidence should be placed in a model's results, given the sources of uncertainty affecting it.