Time-Fixed Covariate
A patient characteristic in a survival model measured once and assumed constant throughout follow-up, such as baseline age or sex.
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A patient characteristic in a survival model measured once and assumed constant throughout follow-up, such as baseline age or sex.
A Markov model in which transition probabilities remain constant throughout the entire modelled time horizon, regardless of how many cycles have passed.
A Markov model in which transition probabilities are allowed to vary over the time horizon, such as mortality risk rising with age.
Outcome data recording the duration until a specific event of interest occurs, such as disease progression or death, possibly censored.
Statistical methods analysing data on the time until a specific event occurs, such as death, while appropriately handling censored observations.
A patient characteristic in a survival model allowed to change value over follow-up, such as a repeatedly measured biomarker.
A hazard rate that changes in magnitude over follow-up, unlike a constant hazard that stays the same at every point.
An interval calculated to contain a specified proportion of an entire population's values with a given confidence, unlike a confidence or prediction interval.
A costing method that starts from total observed expenditure for a programme and divides it by units delivered to produce an average unit cost.
A horizontal bar chart displaying one-way sensitivity analysis results, bars ranked from largest to smallest range, resembling a tornado shape.
A variance-based sensitivity measure quantifying an input's total contribution to output variance, including its individual effect and all interactions with other inputs.
A situation in which achieving more of one objective requires accepting less of another, such as extra health benefit only at extra cost.
A statistical approach identifying and characterising distinct patterns of change in an outcome over time, often revealing subgroups with different courses.
A health state within a Markov model that a patient can leave and potentially return to, unlike an absorbing state such as death.
A table giving the probability of moving from each health state to every other state within one Markov model cycle, each row summing to one.
The likelihood that a patient in a given health state at a cycle's start will move to another state, or stay, by its end.
A cost or outcome value applied at the moment a patient moves between two health states, unlike a state reward accrued over time.
A model explicitly representing how an infectious disease spreads through a population by tracking interaction between infectious and susceptible individuals.
The likelihood that an infectious disease passes from an infected to a susceptible individual during a single contact between them.
A numerical integration technique approximating a definite integral by dividing the area under a curve into trapezoids and summing their areas.