causalis.scenarios.unconfoundedness.refutation.score.score_validation.run_score_diagnosticsrun_score_diagnostics
Run orthogonality and influence diagnostics for ATE or ATTE scores.
The main object is the per-observation score contribution. For ATE, this diagnostic uses
Good score behavior means:
the empirical score average is close to zero,
finite-basis derivatives with respect to nuisance parts are small,
the influence distribution is not driven by a tiny number of very large .
Parameters
- dataCausalData
Dataset used to fit the estimator.
- estimateCausalEstimate
Effect estimate with
diagnostic_datacontaining nuisance predictions and optionally cached score arrays.- overlap_thresholdfloat, optional
Propensity clipping threshold. If omitted, the value is inferred from diagnostic or model metadata.
- n_basis_funcsint, optional
Number of simple basis functions used in orthogonality checks. Defaults to one intercept plus all available confounders.
- return_summarybool, default True
Include a compact summary table in the returned payload.
Returns
Diagnostic report with orthogonality checks, influence summaries, optional out-of-sample tests, and a summary table.
Raises
If required diagnostic arrays are missing or have incompatible shapes.
Examples
Canonical target
causalis.scenarios.unconfoundedness.refutation.score.score_validation.run_score_diagnostics
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