voiage.methods.calibration.voi_calibration

voi_calibration

voi_calibration([positional or keyword] cal_study_modeler: CalibrationStudyModeler | None = None, [positional or keyword] psa_prior: PSASample | None = None, [positional or keyword] calibration_study_design: dict[str, object] | None = None, [positional or keyword] calibration_process_spec: dict[str, object] | None = None, [positional or keyword] population: float | None = None, [positional or keyword] discount_rate: float | None = None, [positional or keyword] time_horizon: float | None = None, [positional or keyword] n_outer_loops: int = 20, [variadic keyword] kwargs: object = {}) -> float

Calculate the value of information for a calibration study.

Parameters

cal_study_modeler : callable, optional Modeler that maps PSA samples and calibration assumptions to net-benefit samples. psa_prior : ParameterSet Prior PSA samples representing current uncertainty. calibration_study_design : dict[str, object] Calibration study design specification. calibration_process_spec : dict[str, object] Calibration process specification. population : float, optional Population size for population scaling. discount_rate : float, optional Annual discount rate used for population scaling. time_horizon : float, optional Time horizon in years for population scaling. n_outer_loops : int, default=20 Number of outer Monte Carlo draws. **kwargs : object Additional modeler-specific options.

Returns

float Calibration VOI on a per-decision basis unless population scaling is requested.

Notes

If no modeler is supplied, the built-in calibration modeler is used.

Parameters:

• cal_study_modeler CalibrationStudyModeler | None (default: None)
• psa_prior PSASample | None (default: None)
• calibration_study_design dict[str, object] | None (default: None)
• calibration_process_spec dict[str, object] | None (default: None)
• population float | None (default: None)
• discount_rate float | None (default: None)
• time_horizon float | None (default: None)
• n_outer_loops int (default: 20)
• kwargs object (default: {})

Returns: float