Fix placebo test examples in README documentation#19
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- Fix fake_timing test: correct post_periods to [3,4,5] instead of [1,2] - Fix fake_group test: add unit parameter and use list of unit IDs instead of query string for fake_treatment_group - Fix permutation test: use binary 'post' column instead of 'period', add required 'unit' parameter - Fix leave_one_out test: use binary 'post' column instead of 'period' - Fix run_all_placebo_tests example: handle error dicts in results iteration, add note about binary post indicator requirement
- Update version in pyproject.toml to match __init__.py - All 249 tests passing - README documentation validated and fixed
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Apr 19, 2026
…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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instead of query string for fake_treatment_group
add required 'unit' parameter
iteration, add note about binary post indicator requirement