Document EfficientDiD covariates+survey deferral in REGISTRY.md from PR #226 review (round 13)

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

Author: igerber

docs/methodology/REGISTRY.md

@@ -678,6 +678,7 @@ where `q_{g,e} = pi_g / sum_{g' in G_{trt,e}} pi_{g'}`.
 - **Note:** Conditional covariance Omega*(X) scales each term by per-unit sieve-estimated inverse propensities s_hat_{g'}(X) = 1/p_{g'}(X) (algorithm step 4), matching Eq 3.12. The inverse propensity estimation uses the same polynomial sieve convex minimization as the ratio estimator. Estimated s_hat values are clipped to [1, n] with a UserWarning when clipping binds, mirroring the ratio path's overlap diagnostics.
 - **Note:** Outcome regressions m_hat_{g',t,tpre}(X) use linear OLS working models. The paper's Section 4 describes flexible nonparametric nuisance estimation (sieve regression, kernel smoothing, or ML methods). The DR property ensures consistency if either the OLS outcome model or the sieve propensity ratio is correctly specified, but the linear OLS specification does not generically guarantee attainment of the semiparametric efficiency bound unless the conditional mean is linear in the covariates.
 - **Note:** EfficientDiD bootstrap with survey weights deferred to Phase 5
+- **Note:** EfficientDiD covariates (DR path) with survey weights deferred — the doubly robust nuisance estimation does not yet thread survey weights through sieve/kernel steps
 
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