causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.unconfoundedness_validation

Unconfoundedness diagnostics for multi-treatment settings.

Module Contents

Functions

run_unconfoundedness_diagnostics	Run multi-treatment unconfoundedness diagnostics from data and estimate.
validate_unconfoundedness_balance	Convenience wrapper returning the balance block only.

Data

__all__

API

causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.unconfoundedness_validation.run_unconfoundedness_diagnostics(data: causalis.data_contracts.multicausaldata.MultiCausalData, estimate: causalis.data_contracts.multicausal_estimate.MultiCausalEstimate, *, threshold: float = 0.1, normalize: Optional[bool] = None, return_summary: bool = True) → Dict[str, Any]

Run multi-treatment unconfoundedness diagnostics from data and estimate.

This implementation currently supports ATE diagnostics only and computes pairwise balance between baseline treatment 0 and each active treatment k.

causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.unconfoundedness_validation.validate_unconfoundedness_balance(data: causalis.data_contracts.multicausaldata.MultiCausalData, estimate: causalis.data_contracts.multicausal_estimate.MultiCausalEstimate, *, threshold: float = 0.1, normalize: Optional[bool] = None) → Dict[str, Any]

Convenience wrapper returning the balance block only.

causalis.scenarios.multi_unconfoundedness.refutation.unconfoundedness.unconfoundedness_validation.__all__

[‘run_unconfoundedness_diagnostics’, ‘validate_unconfoundedness_balance’]