Thread vcov_type through StackedDiD (Phase 1b 2/8)#479
Merged
Conversation
Adds vcov_type ∈ {"classical","hc1","hc2","hc2_bm"} to StackedDiD with
clubSandwich R parity at atol=1e-10 on the hc2_bm path. Defaults to hc1
(prior behavior at machine precision).
Source edits:
- __init__ accepts vcov_type=, rejects classical/hc2 with cluster-
incompatibility ValueError (StackedDiD clusters intrinsically at unit
or unit_subexp; one-way families don't compose with cluster_ids per
the linalg validator), rejects conley with a deferral message.
- fit() rejects survey_design + vcov_type != "hc1" with
NotImplementedError (survey TSL/replicate-refit overrides analytical
sandwich; SA precedent). Reject order locked: fweight/aweight check
fires first, then vcov check (pinned by test_aweight_plus_hc2_bm_*).
- Main solve_ols call at :419: switched from bake-Q-into-X
(X_t = X*sqrt(Q)) to explicit `solve_ols(X, Y, weights=composed_weights,
vcov_type=self.vcov_type)`. solve_ols internally bakes Q for the coef
solve AND back-transforms for vcov on original-scale data via
clubSandwich's WLS-CR2 algebra for hc2_bm (PR #475).
- _refit_stacked closure at :444: mirror switch (cosmetic per
return_vcov=False but grep-consistency).
- StackedDiDResults gains vcov_type field; get_params() includes it.
- llms-full.txt agent-facing entry updated.
R parity:
- benchmarks/data/stacked_did_test_panel.csv (NEW) — pre-stacked panel
generated by extracting StackedDiD's internal stacked_data via the
fixed-seed Python fixture (n_units=50, n_periods=8, cohorts=[3,5,7],
seed=20260521; 325 rows after stacking).
- benchmarks/R/generate_stacked_did_golden.R (NEW) — loads CSV, fits
lm(weights=Q,...) with the same event-study design as Python, computes
CR1S (Stata-style) + CR2-BM SE + BM df_Satt at cluster=unit AND
cluster=unit_subexp via clubSandwich >= 0.7.0.
- benchmarks/data/stacked_did_golden.json (NEW) — committed goldens.
Tests:
- tests/test_stacked_did.py::TestStackedDiDVcovType (19 tests): default
+ bit-equality + reject paths + survey precedence + get_params/set_params
+ result-class field + clone idempotency + replicate-refit smoke +
reject-order regression + unit_subexp + survey symmetric.
- tests/test_methodology_stacked_did.py (4 tests, NEW): hc1 vs CR1S,
hc2_bm vs CR2 (unit), BM DOF vs coef_test()$df_Satt (via t-dist
inversion of CI half-width), hc2_bm vs CR2 (unit_subexp).
- Tolerance note: hc1 vs prior bake-Q-into-X is bit-equal up to ~2 ULPs
at SE scale (multiplication ordering in solve_ols(weights=) vs prior
user-side bake-w); pinned by test_hc1_se_bit_equal_to_pre_pr_baseline
at atol=1e-13.
Docs:
- REGISTRY.md StackedDiD section: new "Variance families" subsection
documenting hc1/hc2_bm routing + rejects, with **Note:** deferring
methodology framing to Phase 1a clubSandwich port (PR #475) — no new
methodology synthesis introduced in this PR.
- CHANGELOG.md: Unreleased Added bullet at top.
- TODO.md: Phase 1b row updated to track remaining 6 estimators; new
StackedDiD conley follow-up row mirroring SA precedent.
234 tests pass across stacked + methodology_stacked_did +
methodology_sun_abraham + methodology_twfe + methodology_wls_cr2 +
estimators_vcov_type.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
… (R1 P0) Local codex R1 caught a P0: StackedDiD(vcov_type="hc2_bm") computed CR2 vcov correctly but never propagated the Bell-McCaffrey Satterthwaite DOF into safe_inference() calls. event_study_effects[h]['p_value']/['conf_int'] and overall_p_value/overall_conf_int silently fell back to normal-theory inference (df=None ⇒ scipy.norm), contradicting the registry contract. Fix mirrors the SunAbraham aggregated-inference pattern from PR #472 (sun_abraham.py:997-1097). After solve_ols(), if vcov_type=="hc2_bm" and not on the survey replicate-refit path, build contrast matrix: - Per-event-time: unit vector at each interaction_indices[h] - Overall ATT: 1/K average across post-period interaction columns Call _compute_cr2_bm_contrast_dof(X, cluster_ids, bread, contrasts, weights=composed_weights). Apply per-event-time DOFs to event_study_effects inference, overall DOF to overall_* inference. Wrap in try/except so any rank-deficient or linalg failure emits a UserWarning and falls back to normal-theory (visible deviation, not silent). R fixture extended with the post-period-average ATT contrast DOF via Wald_test(constraints=row_avg, vcov=CR2, test="HTZ")$df_denom (mirrors PR #465's MPD avg_att approach). New goldens at both cluster=unit and cluster=unit_subexp. Test additions / strengthening (addresses R1 P2 + P3): - test_hc2_bm_per_event_dof_matches_coef_test_df_satt_unit_cluster: uses brentq inversion of CI half-width to recover the DOF safe_inference actually used. If propagation failed (the R1 P0 bug), the inversion raises ValueError → test FAILS instead of silently skipping (replaces the prior `continue`-on-failure pattern which could vacuously pass). Hard-asserts validated_count == len(event_times). - test_hc2_bm_overall_att_dof_matches_wald_test_htz_unit_cluster (NEW): pins overall ATT DOF at atol=1e-6 against R Wald_test(HTZ)$df_denom. - test_hc2_bm_overall_att_dof_matches_wald_test_htz_unit_subexp_cluster (NEW): symmetric coverage at alternate cluster level. - Renamed CR1 → CR1S throughout docs/tests/REGISTRY for consistency (diff-diff's HC1+cluster uses Stata-style G/(G-1)*(n-1)/(n-p); plain CR1 omits the (n-1)/(n-p) term and diverges by ~1.4%). 192 tests pass (74 stacked + 19 wls_cr2 + 47 SA + 52 estimators_vcov_type). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Local codex R2 caught a P1: on rank-deficient stacked designs, the BM contrast DOF block called `_compute_cr2_bm_contrast_dof()` on the singular full bread matrix, which raised LinAlgError and triggered the catch-and- fallback path — downgrading the aggregated inference to normal-theory even when the target event-time delta_h coefficients were still identified. Fix mirrors the MultiPeriodDiD rank-deficient pattern (PR #465, estimators.py:1860-1913): - Derive `_identified = ~np.isnan(coef)` (solve_ols emits NaN for dropped columns under R-style rank handling). - Subset X, bread, and contrasts to the identified-column block BEFORE calling `_compute_cr2_bm_contrast_dof`. - Only build per-event-time contrasts for event-times whose target delta_h column is identified; only build the overall ATT contrast when ALL post-period delta_h are identified (otherwise the contrast is undefined). - The remaining try/except is a defensive guard for genuine singularities on the identified-column design (rare; the rank-deficient handling already removes the problematic columns). The earlier behavior was too aggressive: a single dropped nuisance column would knock out BM DOF for ALL contrasts. The new behavior NaN-guards only contrasts that target a dropped column. New regression test `test_hc2_bm_rank_deficient_design_keeps_bm_dof_*` — verifies the fit doesn't emit fallback warnings on a well-conditioned design + checks that CI half-widths use t(BM DOF) instead of z=1.96 (catches the R1/R2 normal-fallback failure mode end-to-end). 75 tests pass across stacked + methodology_stacked_did. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Local codex R3 caught a P1 on the same surface: when BM contrast DOF was unavailable (helper raised OR noise-floor NaN guard fired), StackedDiD either fell back to normal-theory inference (silent wrong CIs/p-values under the hc2_bm contract) or passed NaN df through safe_inference (which guards df<=0 but NOT NaN, producing finite t_stat with NaN p/CI — mixed inconsistent inference fields). Both fail-open patterns contradict the registry contract that hc2_bm aggregated inference uses BM DOF. Fix mirrors the LinearRegression.get_inference() pattern from PR #475 R7 (linalg.py:3689-3706): on the hc2_bm path, when the per-contrast BM DOF is None or non-finite, emit ALL-NaN inference fields for that contrast rather than falling back to safe_inference(df=None or NaN). Effect and SE remain finite — only the inference fields downstream of the DOF are suppressed. Applied at both inference sites: - Event-study per-event-time inference (event_study_effects[h]): inline check before safe_inference call. - Overall ATT inference (overall_t/p/conf_int): same guard. New regression tests: - test_hc2_bm_nan_dof_fails_closed_with_all_nan_inference: monkeypatches `_compute_cr2_bm_contrast_dof` to return a NaN-only vector and asserts ALL event-study + overall t_stat/p_value/conf_int are NaN while effect and se remain finite. - test_hc2_bm_helper_raises_fails_closed_with_all_nan_inference: monkeypatches the helper to raise LinAlgError and asserts the fallback path NaN-closes inference (does NOT use normal-theory). 77 tests pass. Pattern is consistent with the analytical-surface fail-closed contract added in PR #475 R7. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…drift lock) R4 verdict was ✅ with 3 polish items: P2: helper-exception warning text was stale (said "Falling back to normal distribution" but the code now NaN-closes per the R3 P1 fix). Rewrote the warning to accurately describe the fail-closed contract: "Aggregated p-values, t-statistics, and confidence intervals will be returned as NaN to preserve the hc2_bm contract". P3: set_params(vcov_type=...) bypassed the __init__ validation guard — sklearn-style mutation could set arbitrary values and fail later in the linalg layer with a different message. Fix: factored the vcov_type validation into `StackedDiD._validate_vcov_type(staticmethod)` and call it from BOTH __init__ AND set_params. New test `test_set_params_revalidates_vcov_type` exercises all 4 reject paths. P3: test_replicate_refit_coef_bit_equal_vs_bake_w_baseline was described as a "drift lock" but only checked finiteness — wouldn't catch numeric drift. Captured baseline overall_att=2.0807833161293945 + overall_se=0.14697256517699428 on the post-PR branch and asserted with atol=1e-13 (coef) / 1e-10 (SE, compounded through replicate-refit variance aggregation). Now the test actually catches drift. 78 tests pass (4 set_params reject paths + strengthened drift lock). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…eficient test)
R5 verdict was ✅ with 2 P3 polish items:
P3 (Maintainability): the new solve_ols(weights=...) call sites relied on
the default weight_type="pweight". Locked the WLS-CR2 weight convention
locally by passing weight_type="pweight" explicitly in BOTH solve_ols
calls (main fit + _refit_stacked replicate closure). Prevents silent
variance-contract drift if solve_ols's default ever changes.
P3 (Docs/Tests): test_hc2_bm_rank_deficient_design_keeps_bm_dof_on_
identified_contrasts didn't actually create a rank-deficient design — it
only verified the t-distribution was used on a well-conditioned fixture.
Two-part fix:
1. Renamed the existing test to
test_hc2_bm_uses_t_distribution_not_normal_on_well_conditioned_design
(honest description: it's an end-to-end smoke check that BM DOF
threading reaches safe_inference).
2. NEW test test_hc2_bm_rank_deficient_keeps_bm_dof_on_identified_
contrasts: monkeypatches solve_ols to inject NaN at the intercept
column, simulating rank deficiency. Exercises the reduced-design
code path at stacked_did.py:529-577 added in the R2 P1 fix.
Verifies: (i) no fallback warning (reduced-design helper succeeds);
(ii) identified delta_h coefficients keep finite t-distribution
inference (CI half-width > z_0.975 * SE); (iii) overall ATT also
keeps t-distribution.
79 tests pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
R6 verdict was ✅ with 2 P3 test-coverage polish items: P3 (test): prior R fixture didn't pin the overall delta-method SE for the post-period-average ATT contrast — only BM DOF. Post-period covariance regressions could slip through. Fix: added `se_overall_cr1` and `se_overall_cr2` to the R fixture (computed as `c @ vcov @ c.T` for the post-period 1/K row contrast at both cluster levels). Added overall_se parity assertions at atol=1e-10 to the three existing hc1/hc2_bm parity tests. P3 (test): the Python parity test regenerated the panel via `generate_staggered_data(...)` instead of cross-checking against the committed CSV. Risk: future DGP-helper drift would silently invalidate R-parity assertions. Fix: added a DGP-drift check in the `panel` fixture that loads `benchmarks/data/stacked_did_test_panel.csv`, merges with the regenerated panel on (unit, period), and asserts the `outcome` column matches at atol=1e-12. Catches any drift in the DGP helper with a clear error message rather than wrong parity output. (first_treat column not checked because inf-vs-0 recoding differs between CSV/pandas-read and regenerated panel; outcome is what actually drives the R-side fit.) 79 tests pass. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…ning R7 verdict was⚠️ Needs changes with one P1 + one P3: P1: BM-DOF logic was only pinned on default (anticipation=0, weighting='aggregate'). The BM-DOF code path uses anticipation in post-period selection (`h >= -self.anticipation`) and consumes the composed Q-weights directly — both surfaces were untested. Added 4 parameter-interaction tests: - test_anticipation_plus_hc2_bm_threads_bm_dof: anticipation=1, asserts shifted reference period (e=-2 has SE=0), overall ATT contrast uses t(BM DOF) (CI half-width > z_0.975 * SE), at least one event-study CI uses t-distribution. - test_population_weighting_plus_hc2_bm_finite_threads_bm_dof: weighting='population' (different Q-weight formula), verifies finite output + BM DOF propagation via t-distribution check. - test_sample_share_weighting_plus_hc2_bm_finite_threads_bm_dof: weighting='sample_share' (third Q-weight formula), symmetric coverage. - test_hc1_vs_hc2_bm_differ_under_anticipation: sanity check that hc1 vs hc2_bm SEs actually differ under anticipation=1 (proves the leverage/DOF adjustment fires under non-default params). These tests don't require R goldens (no methodology change vs default case; just verifies the BM-DOF code path remains active under the parameter variants). R parity on the default path is already strong. P3: fixture-independence concern from R6 was only partially closed. Now also pins the `first_treat` column equality after normalizing inf/0 between CSV (pandas reads inf for never-treated) and regenerated (0 for never-treated in some pandas versions). Catches cohort-assignment drift independently of outcome drift. 83 tests pass (+4 new R7 tests). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
…ion') R8 verdict was⚠️ still Needs changes: R7's parameter-interaction tests were smoke checks (population test used constant pop=1.0 which is numerically degenerate with aggregate weighting on a balanced panel); no R goldens for non-default variants. Closes the gap with numerical parity at atol=1e-10. Source-tree additions: - benchmarks/data/stacked_did_anticipation1_panel.csv (NEW): pre-stacked fixture with anticipation=1, generated from same base panel via StackedDiD(anticipation=1).fit(). Event times [-3,-2,-1,0,1,2] with ref=-2 (shifted by anticipation). - benchmarks/data/stacked_did_population_panel.csv (NEW): pre-stacked fixture with weighting='population' AND heterogeneous unit populations (rng.uniform(1,100), seed=99). Q-weights range [0.68, 1.54] vs uniform ~1.0 under aggregate weighting; forces the population-formula branch. - benchmarks/R/generate_stacked_did_golden.R: refactored to loop over 3 variants (default, population, anticipation1), producing variant-keyed entries in `stacked_did_golden.json`. Post-period filter now generalized to `h >= -anticipation` (matches Python's `_post_event_times_preview` at stacked_did.py:546-548). - benchmarks/data/stacked_did_golden.json: regenerated with all 3 variants. Test additions (tests/test_methodology_stacked_did.py): - new class TestStackedDiDParityRVariants (4 tests): - test_population_weighting_hc1_matches_clubsandwich_cr1s - test_population_weighting_hc2_bm_matches_clubsandwich_cr2 - test_anticipation1_hc1_matches_clubsandwich_cr1s - test_anticipation1_hc2_bm_matches_clubsandwich_cr2 All assert event-study SE AND overall_se at atol=1e-10. - new fixture `population_panel` reproduces the heterogeneous-population seed (np.random.default_rng(99)) used by the R variant CSV generator. 87 tests pass (+4 variant parity). Note: weighting='sample_share' parity not added because its Q-weight formula structurally mirrors population weighting (both differ from aggregate only in the Q-weight calculation, which feeds into the same solve_ols(weights=) path). The population test exercises that code path; sample_share remains covered by the smoke test from R7. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
R9 verdict was⚠️ still on parameter-coverage P1: sample_share had no R-parity fixture, and population/anticipation1 tests asserted SE only (not BM DOF). Source-tree additions: - benchmarks/data/stacked_did_sample_share_panel.csv (NEW): pre-stacked fixture for weighting='sample_share'. - benchmarks/R/generate_stacked_did_golden.R: added sample_share variant to the variants list; loops over all 4 variants now. - benchmarks/data/stacked_did_golden.json: regenerated with sample_share. Test additions (tests/test_methodology_stacked_did.py): - test_sample_share_weighting_hc1_matches_clubsandwich_cr1s - test_sample_share_weighting_hc2_bm_matches_clubsandwich_cr2 (+ DOF) - Extended test_population_weighting_hc2_bm_matches_clubsandwich_cr2: added per-event-time + overall BM DOF parity via CI-width inversion. - Extended test_anticipation1_hc2_bm_matches_clubsandwich_cr2: same DOF parity additions. 89 tests pass. All 3 non-default variants now have full R parity: event-study SE + overall_se + per-event BM DOF + overall BM DOF. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Overall assessment✅ Looks good Executive summary
MethodologyNo unmitigated findings. Cross-checking the change against Code QualityNo unmitigated findings. The new parameter is validated at construction and re-validation time ( Performance
Maintainability
Tech Debt
SecurityNo findings. Documentation/TestsNo unmitigated documentation/test findings in the PR itself. The added coverage is broad across Verification note: I could not run |
CI codex R1 verdict was ✅ with 2 polish items:
P2 (Maintainability): StackedDiDResults.summary() didn't surface the
analytical variance family (vcov_type), even though hc1 vs hc2_bm are
now materially different user-facing inference modes. Other result
classes (DiD/MPD/TWFE) already print a Variance: line via the shared
`_format_vcov_label` helper at results.py:49-89. Fix: added a Variance:
line to StackedDiDResults.summary() using the shared helper, suppressed
under survey_metadata (the survey block already surfaces inference
source). My earlier plan note ("mirror SA: don't add Variance: row")
was based on a wrong assumption — SA-results uses the same shared
helper, and StackedDiD inherits the same precedent.
P3 (Performance): on `vcov_type="hc2_bm"` fits with `aggregate=None`
or `"simple"`, the code built per-event Bell-McCaffrey contrast DOFs
that were never surfaced (only overall ATT is exposed). Avoidable
CR2 cost on every overall-only hc2_bm fit. Fix: gated the per-event
contrast construction (es_keys, es_cols_full) on
`aggregate == "event_study"`. The overall ATT contrast still gets
computed unconditionally (it's the user-facing scalar).
89 tests still pass — no behavioral regression on the event-study
path; overall-only fits are now slightly faster.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
|
🔁 AI review rerun (requested by @igerber) Head SHA: Overall assessment✅ Looks good Executive summary
Methodology
Code QualityNo unmitigated findings. PerformanceNo unmitigated findings. The earlier overall-only CR2-BM extra-work issue appears addressed by gating per-event DOF construction to the event-study path in MaintainabilityNo additional unmitigated findings beyond the summary-metadata issue above. Tech Debt
SecurityNo findings. Documentation/TestsNo additional unmitigated findings in the PR content. I could not run |
R2 verdict was ✅ + 1 P2: the summary's Variance: line (added in R1)
mislabelled clustered StackedDiD fits as one-way ("HC1
heteroskedasticity-robust" / "HC2 + Bell-McCaffrey DOF (one-way, n=N)")
because I passed cluster_name=None to _format_vcov_label. StackedDiD
is intrinsically clustered.
Fix:
- Added `cluster_name` and `n_clusters` fields to StackedDiDResults
dataclass.
- Populated both at fit() time: cluster_name=self.cluster, n_clusters=
np.unique(cluster_ids).size (matches the actual realized count, not
config).
- summary() now passes cluster_name + n_clusters into
_format_vcov_label, rendering "CR1 cluster-robust at unit, G=50"
for hc1 and "CR2 Bell-McCaffrey cluster-robust at unit, G=50" for
hc2_bm.
New regression test test_summary_renders_clustered_variance_label
verifies:
- hc1 → label contains "CR1 cluster-robust at unit"
- hc2_bm → label contains "CR2 Bell-McCaffrey cluster-robust at unit"
- Neither contains "(one-way" (catches the R2 regression directly)
- G= cluster count present
- cluster="unit_subexp" → label contains "at unit_subexp"
90 tests pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
|
🔁 AI review rerun (requested by @igerber) Head SHA: Overall Assessment ✅ Looks good Executive Summary
Methodology
Code Quality
Performance
Maintainability
Tech Debt
Security
Documentation/Tests
|
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Summary
vcov_type ∈ {"hc1","hc2_bm"}through StackedDiD (Phase 1b 2/8 of the standalone-estimator threading initiative). HC1 default preserves prior behavior; hc2_bm routes CR2 Bell-McCaffrey through the clubSandwich WLS-CR2 port merged in PR Lift hc2_bm + weights gates via clubSandwich WLS-CR2 port #475.classical/hc2rejected at__init__(StackedDiD is intrinsically clustered, nocluster=Noneopt-out).conleyrejected with a deferral message.event_study_effects[h]) and overall (overall_p_value/overall_conf_int) aggregated inference via_compute_cr2_bm_contrast_dof; mirrors the SunAbraham aggregated-inference pattern from PR Thread vcov_type through SunAbraham (Phase 1b 1/8) #472.estimators.py:1860-1913).LinearRegression.get_inference()from PR Lift hc2_bm + weights gates via clubSandwich WLS-CR2 port #475 R7).survey_design=combined withvcov_type != "hc1"raisesNotImplementedError. Reject order locked: fweight/aweight check fires first (Q-weight semantics), then vcov check.set_params(vcov_type=...)re-validates via shared_validate_vcov_typehelper (no bypass of__init__guard).atol=1e-10againstclubSandwich::vcovCR(...) + coef_test()$df_Satt+Wald_test(test="HTZ")$df_denomon 4 panel variants: default-aggregate, heterogeneous-population, sample_share, anticipation=1.Methodology references
hc2_bm + weightsrow); no new methodology choice is introduced in this PR.clubSandwich::vcovCR(type="CR1S")(Stata-styleG/(G-1) * (n-1)/(n-p)correction) — NOT plainCR1which omits the(n-1)/(n-p)factor and diverges by ~1.4% on the test fixture. Documented in REGISTRY.Validation
tests/test_methodology_stacked_did.py(NEW, 12 tests covering R parity on 4 variants × hc1/hc2_bm surfaces + DOF parity);tests/test_stacked_did.pyextended withTestStackedDiDVcovType(29 tests: defaults + rejects + clone idempotency + replicate-refit drift lock + rank-deficient handling + fail-closed inference + parameter-interaction smoke tests).benchmarks/R/generate_stacked_did_golden.R(clubSandwich v0.7.0). 4 committed pre-stacked CSV panels.Security / privacy
Test plan
pytest tests/test_methodology_stacked_did.pypytest tests/test_stacked_did.pypytest tests/test_methodology_sun_abraham.py tests/test_methodology_twfe.py tests/test_methodology_wls_cr2.pyfeedback_local_codex_vs_ci_codex_divergence)🤖 Generated with Claude Code