igerber · igerber · Apr 26, 2026 · Apr 25, 2026 · Apr 26, 2026 · Apr 26, 2026
diff --git a/docs/api/had.rst b/docs/api/had.rst
@@ -46,29 +46,75 @@ Unit Remains Untreated" (arXiv:2405.04465v6), which:
    - **Unweighted** - continuous paths use the CCT-2014 weighted-robust SE
      from the in-house ``lprobust`` port; the mass-point path uses a
      structural-residual 2SLS sandwich. No cross-horizon covariance.
-   - **``weights=`` shortcut** - continuous paths reuse the CCT-2014 SE;
-     the mass-point path uses an analytical weighted 2SLS sandwich
-     (``classical`` / ``hc1`` only - ``hc2`` / ``hc2_bm`` raise
-     ``NotImplementedError`` pending a 2SLS-specific leverage derivation).
-   - **``survey=``** - both paths compose Binder (1983) Taylor-series
-     linearization with ``df_survey`` threaded into ``safe_inference``.
+   - **``weights=np.ndarray`` shortcut (deprecated)** - continuous paths
+     reuse the CCT-2014 SE; the mass-point path uses an analytical
+     weighted 2SLS sandwich (``classical`` / ``hc1``; CR1 when
+     ``cluster=`` is supplied, except ``cluster=`` +
+     ``aggregate="event_study"`` + ``cband=True`` is rejected outright
+     regardless of ``vcov_type`` per the cluster-combination deviation
+     below; ``hc2`` / ``hc2_bm`` raise ``NotImplementedError`` pending a
+     2SLS-specific leverage derivation). Yields
+     ``variance_formula="pweight"`` / ``"pweight_2sls"``.
+   - **``survey_design=SurveyDesign(weights="col", ...)``** (canonical;
+     accepts strata / PSU / FPC) - both paths compose Binder (1983)
+     Taylor-series linearization with ``df_survey`` threaded into
+     ``safe_inference``. Yields ``variance_formula="survey_binder_tsl"``
+     / ``"survey_binder_tsl_2sls"``.
+
+   The two weighted paths currently produce different SE families on this
+   estimator (CCT-2014 / 2SLS pweight-sandwich vs Binder-TSL); the
+   deprecated ``weights=`` and ``survey=`` aliases will be removed in the
+   next minor release, at which point the long-term unification onto a
+   single SE contract under ``survey_design=`` lands. (Tracked in
+   ``TODO.md``; the deprecation warning emitted by ``HeterogeneousAdoptionDiD.fit``
+   spells the migration out per call site.) On array-in HAD pretest
+   helpers (``stute_test``, ``yatchew_hr_test``, ``stute_joint_pretest``)
+   the pweight-only shortcut is
+   ``survey_design=make_pweight_design(weights)``; data-in surfaces use
+   ``survey_design=SurveyDesign(weights="col_name", ...)`` against
+   ``data`` instead. ``qug_test`` is the exception: the QUG step has no
+   survey-aware migration target (Phase 4.5 C0 decision; see methodology
+   REGISTRY) and permanently raises ``NotImplementedError`` on any of
+   ``survey_design=`` / ``survey=`` / ``weights=``. The composite
+   workflow ``did_had_pretest_workflow`` handles this by skipping QUG
+   under survey/weighted dispatch and emitting a ``UserWarning``.
 
    A simultaneous confidence band (sup-t) is available only on the
    **weighted event-study path** via ``cband=True``. Joint cross-horizon
    analytical covariance is not computed in this release; tracked in
    ``TODO.md``.
 
    **Mass-point ``vcov_type="classical"`` deviation.** The mass-point
-   ``survey=`` paths (static and event-study) and the ``weights=`` +
-   ``aggregate="event_study"`` + ``cband=True`` path reject
-   ``vcov_type="classical"`` with ``NotImplementedError``. The per-unit
-   2SLS influence function returned by the mass-point fit is HC1-scaled
-   so that ``compute_survey_if_variance`` and the sup-t bootstrap target
+   ``survey_design=SurveyDesign(...)`` paths (static and event-study) and
+   the deprecated ``weights=`` + ``aggregate="event_study"`` +
+   ``cband=True`` path reject ``vcov_type="classical"`` with
+   ``NotImplementedError``. The per-unit 2SLS influence function returned
+   by the mass-point fit is HC1-scaled so that
+   ``compute_survey_if_variance`` and the sup-t bootstrap target
    ``V_HC1`` consistently; mixing it with a classical analytical SE
    would silently report a ``V_HC1``-targeted variance under a
-   ``classical`` label. Use ``vcov_type="hc1"`` (or leave it unset with
-   the default ``robust=True`` mapping); a classical-aligned IF
-   derivation is queued for a follow-up PR.
+   ``classical`` label. Use ``vcov_type="hc1"`` or set ``robust=True``
+   explicitly (the constructor default ``robust=False`` maps to
+   ``vcov_type="classical"``, which triggers the guard); a
+   classical-aligned IF derivation is queued for a follow-up PR.
+
+   **Mass-point cluster-combination deviation.** On
+   ``design="mass_point"``, two clustered weighted paths are rejected
+   outright regardless of ``vcov_type``:
+
+   - ``survey_design=SurveyDesign(...)`` + ``cluster=`` (static and
+     event-study): the survey path composes Binder-TSL variance, which
+     would silently override the CR1 cluster-robust sandwich.
+     Workarounds: ``cluster=`` alone (unweighted CR1), or ``weights=``
+     + ``cluster=`` (weighted-CR1 pweight sandwich), or
+     ``survey_design=`` alone (Binder-TSL). Combined cluster-robust +
+     survey inference is queued for a follow-up PR.
+   - Deprecated ``weights=`` shortcut + ``cluster=`` +
+     ``aggregate="event_study"`` + ``cband=True``: the sup-t bootstrap
+     normalizes HC1-scale perturbations by the CR1 analytical SE,
+     mixing variance families. Workarounds: pass ``cband=False`` (keeps
+     weighted-CR1 per-horizon), or drop ``cluster=`` (keeps
+     weighted-HC1 sup-t).
 
 HeterogeneousAdoptionDiD
 ------------------------
@@ -97,3 +143,63 @@ Multi-period event-study results container for the Appendix B.2 extension.
    :members:
    :undoc-members:
    :show-inheritance:
+
+HAD Pretests
+------------
+
+Diagnostic pretests for the HAD identification assumptions from de Chaisemartin
+et al. (2026). The composite orchestrator
+:func:`~diff_diff.did_had_pretest_workflow` is a diagnostic battery only - it
+does NOT pick the HAD design path (``continuous_at_zero`` /
+``continuous_near_d_lower`` / ``mass_point``); that is auto-detected inside
+:meth:`HeterogeneousAdoptionDiD.fit` from the dose support. The workflow has
+two explicit modes selected by the caller via the ``aggregate=`` kwarg:
+``aggregate="overall"`` (default, two-period first-differenced sample) runs
+single-period tests; ``aggregate="event_study"`` (multi-period panel with
+three or more periods) runs joint multi-period tests. Both modes return a
+unified :class:`~diff_diff.HADPretestReport`.
+
+.. autofunction:: diff_diff.did_had_pretest_workflow
+
+.. autoclass:: diff_diff.HADPretestReport
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Single-period tests (``aggregate="overall"``)
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: diff_diff.qug_test
+
+.. autofunction:: diff_diff.stute_test
+
+.. autofunction:: diff_diff.yatchew_hr_test
+
+.. autoclass:: diff_diff.QUGTestResults
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+.. autoclass:: diff_diff.StuteTestResults
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+.. autoclass:: diff_diff.YatchewTestResults
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Joint multi-period tests (``aggregate="event_study"``)
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: diff_diff.stute_joint_pretest
+
+.. autofunction:: diff_diff.joint_pretrends_test
+
+.. autofunction:: diff_diff.joint_homogeneity_test
+
+.. autoclass:: diff_diff.StuteJointResult
+   :members:
+   :undoc-members:
+   :show-inheritance:
diff --git a/docs/choosing_estimator.rst b/docs/choosing_estimator.rst
@@ -93,6 +93,10 @@ Quick Reference
      - Continuous dose / treatment intensity
      - Strong Parallel Trends (SPT) for dose-response; PT for binarized ATT
      - ATT\ :sup:`loc` (PT); ATT(d), ACRT(d) (SPT)
+   * - ``HeterogeneousAdoptionDiD``
+     - Universal rollout, dose varies, no untreated unit
+     - dCDH 2026 Assumptions (Design 1' QUG case or Design 1 with A6/A5)
+     - WAS or WAS\ :sub:`d_lower` per resolved estimand; event-study Appendix B.2
    * - ``SunAbraham``
      - Staggered adoption, interaction-weighted
      - Conditional parallel trends
@@ -357,6 +361,49 @@ Use :class:`~diff_diff.ContinuousDiD` when:
    print(f"Overall ATT: {results.overall_att:.3f}")
    att_curve = results.dose_response_att.to_dataframe()
 
+Universal Rollout / No Untreated Control
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Use :class:`~diff_diff.HeterogeneousAdoptionDiD` when:
+
+- **Every unit is treated at the post period** (universal-rollout policy,
+  industry-wide tariff change, simultaneous launch into all markets)
+- Treatment **intensity (dose) varies across units**, but no genuinely
+  untreated control group exists to anchor a standard DiD contrast
+- :class:`~diff_diff.ContinuousDiD` is unavailable because its untreated-group
+  requirement (``D = 0``) is violated
+
+The estimator implements de Chaisemartin, Ciccia, D'Haultfoeuille and Knau
+(2026, arXiv:2405.04465v6) and resolves to one of two estimands depending on
+the dose support:
+
+- **Design 1' (QUG case, ``d_lower = 0``)** identifies the **Weighted Average
+  Slope (WAS)** under the Quasi-Untreated-Group assumption (units with the
+  smallest dose serve as the comparison anchor). The shipped result class
+  exposes ``target_parameter == "WAS"``.
+- **Design 1 (no QUG, ``d_lower > 0``)** identifies ``WAS_{d_lower}`` under
+  Assumption 6, or sign identification only under Assumption 5; neither
+  additional assumption is testable via pre-trends. Result class exposes
+  ``target_parameter == "WAS_d_lower"``.
+
+The dose-distribution path is auto-detected. Run
+:func:`~diff_diff.did_had_pretest_workflow` to vet the identifying assumptions
+before estimation; see :doc:`api/had` for the full API and SE-regime contract.
+
+.. code-block:: python
+
+   from diff_diff import HeterogeneousAdoptionDiD, did_had_pretest_workflow
+
+   pretests = did_had_pretest_workflow(data, outcome_col='y', unit_col='unit',
+                                       time_col='period', dose_col='dose')
+
+   est = HeterogeneousAdoptionDiD()
+   results = est.fit(data, outcome_col='y', unit_col='unit',
+                     time_col='period', dose_col='dose')
+
+   print(f"Resolved estimand: {results.target_parameter}")
+   print(f"Estimate: {results.att:.3f}")
+
 Efficient DiD
 ~~~~~~~~~~~~~
 
@@ -615,6 +662,9 @@ differences helps interpret results and choose appropriate inference.
    * - ``ContinuousDiD``
      - Analytical (influence function)
      - Uses influence-function-based SEs by default. Use ``n_bootstrap=199`` (or higher) for multiplier bootstrap inference with proper CIs.
+   * - ``HeterogeneousAdoptionDiD``
+     - Path-dependent (CCT-2014 / 2SLS / Binder TSL)
+     - Three SE regimes per :doc:`api/had`. **Unweighted**: continuous-dose paths use the CCT-2014 weighted-robust SE from the in-house ``lprobust`` port; mass-point uses a 2SLS sandwich. **Deprecated ``weights=`` shortcut**: continuous reuses CCT-2014; mass-point uses analytical weighted 2SLS (``classical`` / ``hc1``; CR1 when ``cluster=`` is supplied, except mass-point + ``cluster=`` + ``aggregate="event_study"`` + ``cband=True`` is rejected outright - see :doc:`api/had` for the cluster-combination deviation note); yields ``variance_formula="pweight"`` / ``"pweight_2sls"``. **``survey_design=SurveyDesign(weights="col", ...)``**: both paths compose Binder (1983) Taylor-series linearization (``"survey_binder_tsl"`` / ``"survey_binder_tsl_2sls"``); mass-point + ``survey_design=`` + ``cluster=`` is also rejected outright (combined survey + cluster inference is deferred). The two weighted families differ on this estimator until the next-minor unification lands. Per-horizon CIs are pointwise; sup-t bands available only on the weighted event-study path via ``cband=True``.
    * - ``SunAbraham``
      - Cluster-robust (unit level)
      - Clusters at unit level by default. Specify ``cluster`` to override. Use ``n_bootstrap`` for pairs bootstrap inference.
@@ -777,6 +827,11 @@ estimation. The depth of support varies by estimator:
      - Full
      - Full (analytical)
      - Multiplier at PSU
+   * - ``HeterogeneousAdoptionDiD``
+     - pweight only
+     - Full (Binder TSL)
+     - --
+     - Multiplier (event-study, ``cband=True`` only)
    * - ``EfficientDiD``
      - Full
      - Full

diff --git a/docs/doc-deps.yaml b/docs/doc-deps.yaml
@@ -385,6 +385,19 @@ sources:
 
   diff_diff/had_pretests.py:
     drift_risk: medium
+    docs:
+      - path: docs/methodology/REGISTRY.md
+        section: "HeterogeneousAdoptionDiD"
+        type: methodology
+      - path: docs/api/had.rst
+        section: "HAD Pretests"
+        type: api_reference
+      - path: diff_diff/guides/llms.txt
+        section: "Estimators"
+        type: user_guide
+
+  diff_diff/local_linear.py:
+    drift_risk: low
     docs:
       - path: docs/methodology/REGISTRY.md
         section: "HeterogeneousAdoptionDiD"

diff --git a/docs/practitioner_decision_tree.rst b/docs/practitioner_decision_tree.rst
@@ -44,6 +44,11 @@ Which of these best describes your situation?
    Your outcome comes from a survey with complex sampling. Go to
    :ref:`section-survey`.
 
+7. **All my markets received the campaign at the same time, but spend levels varied** (no untreated control market exists)
+
+   Universal rollout with dose-only variation. Go to
+   :ref:`section-no-untreated`.
+
 .. tip::
 
    In academic literature, "rolling out in waves" is called *staggered adoption*,
@@ -258,6 +263,54 @@ appropriate identification assumptions in place.
    require Strong Parallel Trends (see warning above).
 
 
+.. _section-no-untreated:
+
+Universal Rollout (No Untreated Markets)
+----------------------------------------
+
+**Your situation:** Every market got the campaign at the same time - there is no
+holdout group - but spending levels varied across markets. ``ContinuousDiD`` cannot
+help here because it requires an untreated comparison group; standard DiD has no
+control to anchor the contrast.
+
+**Recommended method:** :class:`~diff_diff.HeterogeneousAdoptionDiD`
+
+This estimator implements de Chaisemartin, Ciccia, D'Haultfoeuille and Knau (2026)
+and resolves to one of two estimands depending on whether the smallest-dose
+markets can serve as a quasi-untreated anchor (Design 1') or whether the
+identification rests on stronger structural assumptions (Design 1).
+
+.. code-block:: python
+
+   from diff_diff import HeterogeneousAdoptionDiD, did_had_pretest_workflow
+
+   # Run the pretest battery first - it surfaces violations of the HAD
+   # identification assumptions (it does NOT pick the design path; the
+   # estimator does that internally from the dose support).
+   pretests = did_had_pretest_workflow(
+       data, outcome_col="y", unit_col="unit",
+       time_col="period", dose_col="dose",
+   )
+   print(pretests)
+
+   est = HeterogeneousAdoptionDiD()
+   results = est.fit(
+       data, outcome_col="y", unit_col="unit",
+       time_col="period", dose_col="dose",
+   )
+   print(f"Resolved estimand: {results.target_parameter}")
+   print(f"Average lift per unit of dose: {results.att:.2f}")
+
+.. note::
+
+   **Academic term:** The estimator targets the *Weighted Average Slope (WAS)* under
+   the QUG / Design 1' case, or *WAS_{d_lower}* under Design 1. Neither identifying
+   assumption is testable via pre-trends alone - run
+   :func:`~diff_diff.did_had_pretest_workflow` for the recommended battery. See
+   :doc:`api/had` for the inference contract (three SE regimes; pointwise CIs;
+   sup-t bands only on the weighted event-study path).
+
+
 .. _section-few-markets:
 
 Few Test Markets
@@ -377,6 +430,9 @@ At a Glance
    * - Varied spending levels
      - ``ContinuousDiD``
      - Dose-response curve
+   * - Universal rollout, no untreated markets
+     - ``HeterogeneousAdoptionDiD``
+     - Targets WAS / WAS_{d_lower} when no holdout exists
    * - Only a few test markets
      - ``SyntheticDiD``
      - Optimal with few treated units