Runge-Kutta Method
A family of numerical methods for solving ordinary differential equations by combining multiple estimates within each step to improve accuracy.
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A family of numerical methods for solving ordinary differential equations by combining multiple estimates within each step to improve accuracy.
The process of determining the number of participants a study needs to have an adequate chance of detecting a specified treatment effect.
The process of determining the number of trial participants needed to reliably detect a treatment effect of a specified, meaningful size.
A method calculating an estimator's variance that remains valid even when standard model assumptions are violated, forming the basis of robust standard errors.
A measure of whether a provider is operating at its optimal size, distinct from whether it uses its current scale of inputs efficiently.
A diagnostic technique testing the proportional hazards assumption by scaling Schoenfeld residuals by their variance to improve test power.
The fundamental economic condition in which available resources are insufficient to satisfy all competing wants and needs.
A form of sensitivity analysis examining how results change under a small number of alternative, internally consistent assumption sets, rather than varying parameters independently.
A residual specific to the Cox model, calculated at each event time, used to test whether the proportional hazards assumption holds.
A measure of whether producing multiple services jointly within one organisation is more efficient than producing them separately across different organisations.
A body of theory analysing how an uninformed party can design a menu of options that leads individuals to reveal their private information through choice.
An iterative root-finding method that approximates the derivative using two previous estimates to locate a function's root.
A measure of infectious disease transmission, the proportion of susceptible close contacts of a primary case who themselves become infected.
An extension of the basic epidemic model adding an exposed compartment for individuals infected but not yet infectious, before they become infectious.
A missing data modelling approach explicitly modelling the process by which observations become missing, alongside the model for the outcome itself.
A category of survival models, notably the Cox model, that assumes covariate effects parametrically while leaving the baseline hazard unspecified.
The proportion of individuals who truly have a condition who are correctly identified as positive by a diagnostic test.
A general term for any technique assessing how a model's results change in response to variation in its inputs or structural assumptions.
The capacity of a health outcome measure to register a difference in health status when a real change has occurred in a patient's condition.
A measure of the frequency of unexpected occurrences involving death or serious injury unrelated to a patient's underlying illness.