Terms for building and checking decision models, including decision trees, Markov models and simulation methods.
A Markov model is a state-transition model in which a cohort or individuals move among mutually exclusive health states over repeated cycles, with future transitions determined by the current state under the model’s memory assumptions.
Microsimulation models individuals one at a time, allowing their characteristics and event histories to influence future outcomes.
A simplifying premise built into a model's structure or parameter values, adopted because the true underlying reality is unknown or too complex.
The initial stage of model development in which the disease process and decision problem are structured into a framework before technical build.
The overall organisation of a health economic model, including its technique, the health states or events represented, and how they link together.
The degree to which a model's structure, assumptions, and calculations are made accessible and understandable to external reviewers.
Model validation is the structured assessment of whether a model is sufficiently accurate, credible, and fit for its stated decision purpose.
An oncology modelling technique estimating the proportion of a cohort in each health state using separately fitted survival curves for different endpoints, rather than modelling transitions.