Mixed Effects Model
A modelling approach including both fixed effects for average relationships and random effects for individual variation, suited to nested or repeated data.
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.
A modelling approach including both fixed effects for average relationships and random effects for individual variation, suited to nested or repeated data.
A longitudinal trial analysis method using a mixed effects framework under the missing at random assumption, an alternative to last observation carried forward.
A cure model treating the population as a mixture of a cured fraction facing only background mortality and an uncured fraction remaining at risk.
A statistical model representing a population as a combination of two or more distinct subgroups, each following its own underlying distribution.
A central tendency measure representing the most frequently occurring value within a dataset.
A statistical technique combining predictions from several plausible candidate models, weighted by their relative statistical support, rather than relying on one selected model.
A set of statistical and technical checks assessing a model's performance, such as poor calibration or unstable results under minor input changes.
The degree to which a statistical or structural model's predictions correspond to observed data, used to judge whether a specification is adequate.
The process of choosing among alternative model structures or specifications for an evaluation, guided by fit, clinical plausibility, and parsimony.
The overall process of establishing confidence that a model's structure and results adequately represent the real-world system it is meant to capture.
A statistical approach examining whether an exposure-outcome relationship's strength or direction differs depending on the level of a third, moderating variable.
A cost analysis incorporating current data sources, such as electronic health records and administrative claims, into estimating resource use.
The pricing behaviour of a firm with monopoly power, setting price above marginal cost to maximise profit and reduce quantity supplied.
The statistical imprecision in a simulation estimate from using a finite number of iterations, distinct from the underlying parameter uncertainty being characterised.
A numerical technique estimating a complex integral's value by sampling random points repeatedly and averaging them, useful when no closed-form solution exists.
A technique estimating a model's output under uncertainty by repeatedly sampling random values for its inputs from specified distributions across many iterations.
Moral hazard occurs when protection from the consequences of an action changes a person’s behaviour because some resulting costs or risks are borne by another party.
A global sensitivity analysis technique efficiently screening many input parameters for negligible, linear, or interactive effects, using relatively few model runs.
An optimisation approach used when a decision involves competing objectives, such as maximising benefit while minimising cost, producing a set of trade-off solutions.
A condition in which two or more regression predictors are highly correlated with one another, making individual effect estimates unreliable.