Nelder-Mead Method
The Nelder-Mead method is a derivative-free algorithm that moves a simplex of trial points to minimise a score, used to calibrate health economic models.
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.
Nelson-Aalen Estimator
The Nelson-Aalen estimator gives a non-parametric cumulative hazard from censored survival data, used to check survival curves in health economic models.
Net Survival Model
A survival model estimating the survival a population would experience if the disease studied were the only possible cause of death.
Newton-Raphson Method
The Newton–Raphson method is an iterative numerical algorithm that uses local derivative information to find a root of an equation.
Non-Mixture Cure Model
A non-mixture cure model is a survival model used in HTA whose survival curve levels off at the cure fraction without splitting patients into two groups.
Non-Parametric Estimation
Non-parametric estimation derives a survival curve or other distribution from observed data, as Kaplan-Meier does, with no assumed mathematical form.
Non-Parametric Survival
Non-parametric survival is a survival estimate taken directly from observed time-to-event data, such as a Kaplan-Meier curve, with no assumed distribution.
Normal Distribution
The normal distribution is a symmetric bell-shaped curve set by a mean and standard deviation, used in health economics for estimated means and log ratios.
Numerical Integration
Numerical integration approximates the area represented by a definite integral when an exact antiderivative is unavailable, inconvenient or evaluated from discrete data.
Numerical Method
A numerical method is a systematic computational procedure that approximates the solution of a mathematical problem through finite arithmetic operations, with accuracy assessed through error, convergence, stability, and conditioning.
Numerical Optimisation
Numerical optimisation uses iterative computational methods to find decision or parameter values that minimise or maximise an objective function.
One-Way Sensitivity Analysis
One-way sensitivity analysis (OWSA) varies one model input at a time, holding the rest at base case, to show which inputs drive cost-effectiveness results.
Optimal Sample Size
A study sample size selected to meet a stated design objective, such as adequate power or precision, or to maximise the expected value of information after accounting for research costs and decision delays.
Parameter Distribution
A parameter distribution is a probability distribution describing uncertainty in the true value of a health economic model input, used in PSA.
Parameter Estimation
Parameter estimation is the process of using evidence and a specified model or estimating rule to infer the values of quantities needed to describe a population, relationship, or decision model.
Parameter Input
A parameter input (model parameter) is a value or distribution entered into a health economic model for a quantity such as a probability, cost or utility.
Parameter Uncertainty
Parameter uncertainty is uncertainty in the estimated values of a health economic model's inputs, such as treatment effects, costs and utilities.
Parametric Estimation
A statistical approach estimating a survival function by assuming the data follow a specific distribution, such as Weibull or log-normal, with estimated parameters.
Parametric Survival
Survival estimates derived from a fitted mathematical distribution rather than directly from observed data alone, allowing extrapolation beyond the data.
Parametric Survival Model
A parametric survival model specifies a probability distribution for time to a defined event, enabling estimation of survival and hazard functions and projection beyond observed follow-up under stated assumptions.