Accept numpy integers in cohort_periods and add tutorial cross-references

- Accept np.integer alongside int in cohort_periods validation,
  matching the existing generate_staggered_data() behavior (P2)
- Add regression test for numpy integer cohort periods
- Add tutorial 16 cross-links in README.md, quickstart.rst, and
  choosing_estimator.rst for discoverability (P3)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: igerber

README.md

@@ -140,6 +140,7 @@ We provide Jupyter notebook tutorials in `docs/tutorials/`:
 | `12_two_stage_did.ipynb` | Two-Stage DiD (Gardner 2022), GMM sandwich variance, per-observation effects |
 | `13_stacked_did.ipynb` | Stacked DiD (Wing et al. 2024), Q-weights, sub-experiment inspection, trimming, clean control definitions |
 | `15_efficient_did.ipynb` | Efficient DiD (Chen et al. 2025), optimal weighting, PT-All vs PT-Post, efficiency gains, bootstrap inference |
+| `16_survey_did.ipynb` | Survey-aware DiD with complex sampling designs (strata, PSU, FPC, weights), replicate weights, subpopulation analysis, DEFF diagnostics |
 
 ## Data Preparation
 

diff_diff/prep_dgp.py

@@ -1223,7 +1223,7 @@ def generate_survey_did_data(
     if not cohort_periods:
         raise ValueError("cohort_periods must be a non-empty list of integers")
     for cp in cohort_periods:
-        if not isinstance(cp, int) or isinstance(cp, bool):
+        if isinstance(cp, bool) or not isinstance(cp, (int, np.integer)):
             raise ValueError(
                 f"cohort_periods must contain integers, got {cp!r}"
             )

docs/choosing_estimator.rst

@@ -569,3 +569,7 @@ If you're unsure which estimator to use:
 
 4. **Compare estimators** - If results differ substantially across estimators,
    investigate why (often reveals violations of assumptions)
+
+5. **Using survey data?** - Pass a ``SurveyDesign`` to ``fit()`` for design-based
+   variance estimation. See the `survey tutorial <https://github.com/igerber/diff-diff/blob/main/docs/tutorials/16_survey_did.ipynb>`_
+   for a full walkthrough with strata, PSU, FPC, replicate weights, and subpopulation analysis.

docs/quickstart.rst

@@ -205,3 +205,4 @@ Next Steps
 - :doc:`choosing_estimator` - Learn which estimator to use for your design
 - :doc:`r_comparison` - See how diff-diff compares to R packages
 - :doc:`api/index` - Explore the full API reference
+- `Survey-aware DiD tutorial <https://github.com/igerber/diff-diff/blob/main/docs/tutorials/16_survey_did.ipynb>`_ - Using DiD with complex survey designs (strata, PSU, FPC, weights)

tests/test_prep.py

@@ -1372,3 +1372,11 @@ def test_cohort_period_non_integer(self):
 
         with pytest.raises(ValueError, match="must contain integers"):
             generate_survey_did_data(cohort_periods=[2.5], seed=42)
+
+    def test_numpy_integer_cohort_periods(self):
+        """Test that numpy integer cohort periods are accepted."""
+        from diff_diff.prep import generate_survey_did_data
+
+        periods = np.array([3, 5], dtype=np.int64)
+        data = generate_survey_did_data(cohort_periods=list(periods), seed=42)
+        assert len(data) == 200 * 8