Extend power analysis to all estimators + simulation-based MDE/sample size

TODO.md

@@ -47,6 +47,7 @@ Deferred items from PR reviews that were not addressed before merge.
 | Bootstrap NaN-gating gap: manual SE/CI/p-value without non-finite filtering or SE<=0 guard | `imputation_bootstrap.py`, `two_stage_bootstrap.py` | #177 | Medium — migrate to `compute_effect_bootstrap_stats` from `bootstrap_utils.py` |
 | EfficientDiD: warn when cohort share is very small (< 2 units or < 1% of sample) — inverted in Omega*/EIF | `efficient_did_weights.py` | #192 | Low |
 | EfficientDiD: API docs / tutorial page for new public estimator | `docs/` | #192 | Medium |
+| TripleDifference power: `generate_ddd_data` is a fixed 2×2×2 cross-sectional DGP — no multi-period or unbalanced-group support. Add a `generate_ddd_panel_data` for panel DDD power analysis. | `prep_dgp.py`, `power.py` | #208 | Low |
 
 #### Performance
 

diff_diff/__init__.py

@@ -53,11 +53,15 @@
 from diff_diff.power import (
     PowerAnalysis,
     PowerResults,
+    SimulationMDEResults,
     SimulationPowerResults,
+    SimulationSampleSizeResults,
     compute_mde,
     compute_power,
     compute_sample_size,
+    simulate_mde,
     simulate_power,
+    simulate_sample_size,
 )
 from diff_diff.pretrends import (
     PreTrendsPower,
@@ -291,11 +295,15 @@
     # Power analysis
     "PowerAnalysis",
     "PowerResults",
+    "SimulationMDEResults",
     "SimulationPowerResults",
+    "SimulationSampleSizeResults",
     "compute_mde",
     "compute_power",
     "compute_sample_size",
+    "simulate_mde",
     "simulate_power",
+    "simulate_sample_size",
     "plot_power_curve",
     # Pre-trends power analysis
     "PreTrendsPower",