voiage.methods.observational.basic_observational_study_modeler
basic_observational_study_modeler
Section titled “basic_observational_study_modeler”basic_observational_study_modeler([positional or keyword] psa_prior: PSASample = None, [positional or keyword] observational_study_design: dict[str, object] = None, [positional or keyword] bias_models: dict[str, object] = None) -> NetBenefitArrayModel a simple observational study update for explicit net benefits.
Parameters
Section titled “Parameters”psa_prior : ParameterSet Prior parameter samples. observational_study_design : dict[str, object] Study design specification, including optional sample size and truth. bias_models : dict[str, object] Bias-model specification used to adjust residual uncertainty.
Returns
Section titled “Returns”ValueArray Net-benefit samples after observational updating.
The built-in modeler accepts explicit strategy net-benefit arrays or matched cost/effect arrays and shrinks uncertainty toward the sampled truth.
Parameters:
psa_priorPSASampleobservational_study_designdict[str, object]bias_modelsdict[str, object]
Returns: NetBenefitArray