Particle Filter
A sequential Monte Carlo algorithm that approximates the evolving probability distribution of a hidden state with weighted simulated particles, updating their weights as observations arrive.
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 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.
A sequential Monte Carlo algorithm that approximates the evolving probability distribution of a hidden state with weighted simulated particles, updating their weights as observations arrive.
Particle swarm optimisation (PSO) is a search method that moves candidate solutions towards the best ones found, used to calibrate health economic models.
A partitioned survival model is a cancer economic model that uses PFS and OS curves to split a cohort into progression-free, progressed and dead states.
A permutation test is a hypothesis test that reshuffles treatment labels between trial patients to see how often a cost or outcome gap this large arises.
The Peto test is a weighted log-rank test comparing survival between groups, weighting each event time by pooled survival so earlier events count more.
A piecewise model is a survival model used in economic evaluation that splits follow-up at cut points and fits a separate hazard within each interval.
A point estimate is a single value calculated from data, such as a mean cost or hazard ratio, offered as the best estimate of an unknown parameter.
Population EVPI is the expected value of perfect information scaled up to all patients a health care decision will affect, discounted over its lifetime.
Probabilistic sensitivity analysis (PSA) runs a decision model many times on jointly drawn inputs to estimate expected outcomes and decision uncertainty.
Probability is a number between 0 and 1 showing how likely an event is, used in health economic models to weight costs and QALYs and express uncertainty.
The proportional hazards assumption is that the hazard ratio between groups, such as trial arms, is constant over follow-up while each hazard may change.
A pseudo-random number is a value produced by a deterministic algorithm whose sequence is designed to exhibit specified statistical properties of random draws.
A queuing model is a mathematical representation of how arrivals, service times, capacity, and service rules generate waiting, congestion, and throughput in a service system.
Random number generation supplies the uncertain draws used in probabilistic sensitivity analysis, microsimulation, discrete-event simulation, bootstrap procedures, and other stochastic analyses.
The mathematical transformation converting a continuous-time hazard rate into the probability of an event occurring within a discrete time interval.
Relative survival is patients' observed survival divided by the expected survival of a matched general population, used in cancer registries and models.
A statistical model estimating disease-specific survival by comparing observed survival against expected general population survival, without individual cause-of-death data.
Response surface methodology fits a polynomial to planned runs of a health economic model so outputs such as net benefit can be predicted and optimised.
A restricted cubic spline is a smooth piecewise cubic function of a continuous predictor constrained to be linear beyond its outer knots, allowing regression models to represent nonlinear associations without prescribing one global polynomial shape.
Restricted mean survival time (RMST) is the mean event-free time up to a set horizon, the area under the survival curve, used to compare treatments in HTA.