Table 1.
Term | Description |
---|---|
Context of use – COU | A statement that defines the specific role and scope of the computational model used to address a question of interest (ASME, 2018).a |
Verification | The process of determining that a computational model accurately represents the underlying mathematical model and its solution (ASME, 2018).b |
Validation | The process of determining the degree to which a model or a simulation is an accurate representation of the real world. |
Sensitivity analysis | The process of determining how a change in a model input (e.g., parameters or initial conditions) affects model outputs. |
Identifiability analysis | The process of determining the reliability of parameter estimates from model structure and experimental data. |
Calibration | The process of tuning or optimizing parameters in a computational model to minimize the difference between model outputs and real world data. |
Uncertainty quantification – UQ | The process of determining the uncertainty in model inputs (e.g., parameters or initial conditions) and computing the resultant uncertainty in model outputs (ASME, 2018).c |
Applicability analysis | The process of assessing the relevance of the validation activities for a computational model to support the use of that model for a COU (ASME, 2018).d |
Additional comments are provided in the footnote. a The COU can also include the other sources of evidence that will support the question of interest. b Verification activities are outside the scope of our review. c Common reasons for uncertainty in model inputs are measurement error or inter-/intra-individual variability. d Detailed discussion in Pathmanathan et al. (2017). UQ usually involves quantifying such uncertainty using probability distributions.