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The documented output values were incorrect. Updated to match actual output from running the Quick Start example code (ATT=3.0, SE=1.7321, p=0.1583).
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…aths Addresses findings #17, #18, #19 from the Phase 2 silent-failures audit (axis A, all Minor). Each site previously ran np.linalg.solve against a matrix that could be rank-deficient or near-singular with no user-facing signal. - StaggeredTripleDifference: `_compute_did_panel` now appends a condition-number sample to an instance tracker on LinAlgError; `fit()` emits ONE aggregate UserWarning listing affected (g, g_c, t) cells and the max condition number instead of silently falling back to np.linalg.lstsq per pair. Tracker resets on repeat fit. - EfficientDiD covariate sieve (estimate_propensity_ratio_sieve, estimate_inverse_propensity_sieve): precondition-check the normal-equations matrix via np.linalg.cond before solve and reject K values above 1/sqrt(eps); partial-K skips now surface via UserWarning listing the skipped K values, instead of being swallowed by `continue`. - compute_survey_vcov: check cond(X'WX) before the sandwich solve; emit UserWarning above the 1/sqrt(eps) threshold so ill-conditioned bread matrices don't silently produce unstable variance estimates. Sibling sites picked up via repo-wide lstsq-fallback pattern grep (per the pattern-check feedback memory): - two_stage.py:1768 (TSL variance bread) - two_stage_bootstrap.py:197 (multiplier bootstrap bread) Both now warn before the silent lstsq fallback. Adds 8 targeted tests across test_staggered_triple_diff.py, test_efficient_did.py, and test_survey.py, covering collinear/ill-conditioned triggers and happy-path negatives. REGISTRY.md notes added for each affected estimator section. No behavioral change on well-conditioned inputs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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…oStage tests CI review on PR #334 flagged one P1 (incomplete audit of silent solve fallbacks) and two P3s. P1 — Callaway-Sant'Anna `_safe_inv()` sibling site: The shared `_safe_inv(A)` helper in staggered.py was still silently falling back from np.linalg.solve to np.linalg.lstsq. It feeds ~13 analytical SE paths (propensity-score Hessian, OR bread, event-study bread, etc.), so a rank-deficient design could silently ship degraded analytical SEs. Extended `_safe_inv(A, tracker: Optional[list] = None)` to append a condition-number sample on LinAlgError when a tracker is passed. Initialize `self._safe_inv_tracker: List[float] = []` at the top of `CallawaySantAnna.fit()`, thread `tracker=self._safe_inv_tracker` through all 13 callsites, and emit ONE aggregate UserWarning at the end of fit() listing the number of fallbacks and max condition number. Matches the tracker pattern established in STD finding #17. Added TestCallawaySantAnnaSafeInvFallback with two tests: collinear covariates trigger the aggregate warning; well-conditioned data emits no warning (happy-path regression guard). REGISTRY.md §CallawaySantAnna notes the new warning contract. P3 — Sieve docstrings lag behavior: Updated estimate_propensity_ratio_sieve and estimate_inverse_propensity_sieve docstrings to describe the new cond(A) > 1/sqrt(eps) precondition check, the partial-K skip warning, and the all-K fallback semantics. P3 — No TwoStage regression coverage: Added TestTwoStageStage2BreadWarning with two tests covering both the analytical TSL and bootstrap bread paths (contract: if the lstsq fallback triggers, it must warn). TODO.md: logged honest_did.py:1907 basis-enumeration skip as an intentional algorithm behavior (not a silent failure per the Phase 2 audit definition) but notable for a future diagnostic enhancement. No behavioral change on well-conditioned inputs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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The documented output values were incorrect. Updated to match actual output from running the Quick Start example code (ATT=3.0, SE=1.7321, p=0.1583).