- P1 #1: _compute_heterogeneity_test now accepts obs_survey_info and
  runs survey-aware WLS + Binder TSL IF when survey_design is active.
  Point estimate via solve_ols(weights=W_elig, weight_type='pweight');
  group-level IF ψ_g[X] = inv(X'WX)[1,:] @ x_g * W_g * r_g, expanded
  to obs-level via w_i/W_g ratio, then compute_survey_if_variance for
  stratified/PSU variance. safe_inference uses df_survey.
  Rank-deficiency short-circuits to NaN to avoid point-estimate/IF
  mismatch between solve_ols's R-style drop and pinv's minimum-norm.
- P1 #2: twowayfeweights() now accepts Optional[SurveyDesign]. When
  provided, resolves weights via _resolve_survey_for_fit and passes
  them to _validate_and_aggregate_to_cells, restoring fit-vs-helper
  parity under survey-backed inputs. fweight/aweight rejected.
- P3: REGISTRY updates — TWFE parity sentence now includes survey;
  heterogeneity Note documents the TSL IF mechanics and library
  extension disclaimer; checklist line-651 lists survey-aware
  surfaces; new survey+bootstrap-fallback Note after line 652.
- P2: 5 new regression tests in test_survey_dcdh.py:
  TestSurveyHeterogeneity (uniform-weights match, non-uniform beta
  change, t-dist df_survey) and TestSurveyTWFEParity (fit-vs-helper
  match, non-pweight rejection).

All 254 targeted tests pass.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

- P1 #1: _compute_twfe_diagnostic now uses cell_weight (w_gt when
  available, else n_gt) for FE regressions, the normalization
  denominator, contribution weights, and the Corollary 1 observation
  shares. On survey-backed inputs the outputs now match the
  observation-level pweighted TWFE estimand; non-survey path is
  byte-identical.
- P1 #2: Zero-weight rows are dropped before the groupby in
  _validate_and_aggregate_to_cells when weights are provided, so that
  d_min/d_max/n_gt reflect the effective sample. Prevents zero-weight
  subpopulation rows from tripping the fuzzy-DiD guard or inflating
  downstream n_gt counts.
- P2: 2 new regression tests in test_survey_dcdh.py —
  TestSurveyTWFEOracle.test_survey_twfe_matches_obs_level_pweighted_ols
  verifies beta_fe matches an observation-level pweighted OLS under
  survey (would fail if n_gt was still used), and
  TestZeroWeightSubpopulation.test_mixed_zero_weight_row_excluded_from_validation
  verifies an injected zero-weight row with opposite treatment value
  doesn't trip the within-cell constancy check.

All 256 targeted tests pass.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

- P1 #1: _compute_heterogeneity_test now accepts obs_survey_info and
  runs survey-aware WLS + Binder TSL IF when survey_design is active.
  Point estimate via solve_ols(weights=W_elig, weight_type='pweight');
  group-level IF ψ_g[X] = inv(X'WX)[1,:] @ x_g * W_g * r_g, expanded
  to obs-level via w_i/W_g ratio, then compute_survey_if_variance for
  stratified/PSU variance. safe_inference uses df_survey.
  Rank-deficiency short-circuits to NaN to avoid point-estimate/IF
  mismatch between solve_ols's R-style drop and pinv's minimum-norm.
- P1 #2: twowayfeweights() now accepts Optional[SurveyDesign]. When
  provided, resolves weights via _resolve_survey_for_fit and passes
  them to _validate_and_aggregate_to_cells, restoring fit-vs-helper
  parity under survey-backed inputs. fweight/aweight rejected.
- P3: REGISTRY updates — TWFE parity sentence now includes survey;
  heterogeneity Note documents the TSL IF mechanics and library
  extension disclaimer; checklist line-651 lists survey-aware
  surfaces; new survey+bootstrap-fallback Note after line 652.
- P2: 5 new regression tests in test_survey_dcdh.py:
  TestSurveyHeterogeneity (uniform-weights match, non-uniform beta
  change, t-dist df_survey) and TestSurveyTWFEParity (fit-vs-helper
  match, non-pweight rejection).

All 254 targeted tests pass.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

- P1 #1: _compute_twfe_diagnostic now uses cell_weight (w_gt when
  available, else n_gt) for FE regressions, the normalization
  denominator, contribution weights, and the Corollary 1 observation
  shares. On survey-backed inputs the outputs now match the
  observation-level pweighted TWFE estimand; non-survey path is
  byte-identical.
- P1 #2: Zero-weight rows are dropped before the groupby in
  _validate_and_aggregate_to_cells when weights are provided, so that
  d_min/d_max/n_gt reflect the effective sample. Prevents zero-weight
  subpopulation rows from tripping the fuzzy-DiD guard or inflating
  downstream n_gt counts.
- P2: 2 new regression tests in test_survey_dcdh.py —
  TestSurveyTWFEOracle.test_survey_twfe_matches_obs_level_pweighted_ols
  verifies beta_fe matches an observation-level pweighted OLS under
  survey (would fail if n_gt was still used), and
  TestZeroWeightSubpopulation.test_mixed_zero_weight_row_excluded_from_validation
  verifies an injected zero-weight row with opposite treatment value
  doesn't trip the within-cell constancy check.

All 256 targeted tests pass.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

- P1 #1/#2: Add _validate_group_constant_strata_psu() helper and call
  it from fit() after the weight_type/replicate-weights checks. The
  dCDH IF expansion psi_i = U[g] * (w_i / W_g) treats each group as
  the effective sampling unit; when strata or PSU vary within group it
  silently spreads horizon-specific IF mass across observations in
  different PSUs, contaminating the stratified-PSU variance. Walk back
  the overstated claim at the old line 669 comment to match. Within-
  group-varying weights remain supported.
- P1 #3: _survey_se_from_group_if now filters zero-weight rows before
  np.unique/np.bincount so NaN / non-comparable group IDs on excluded
  subpopulation rows cannot crash SE factorization. psi stays full-
  length with zeros in excluded positions to preserve alignment with
  resolved.strata / resolved.psu inside compute_survey_if_variance.
- REGISTRY.md line 652 Note updated: explicitly states the
  within-group-constant strata/PSU requirement and the
  within-group-varying weights support.
- Tests: new TestSurveyWithinGroupValidation class (4 tests — rejects
  varying PSU, rejects varying strata, accepts varying weights, and
  ignores zero-weight rows during the constancy check) plus
  TestZeroWeightSubpopulation.test_zero_weight_row_with_nan_group_id.

All 268 targeted tests pass.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>