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Copy file name to clipboardExpand all lines: CHANGELOG.md
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## [Unreleased]
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## [2.9.1] - 2026-04-06
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### Added
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-**Survey theory document** (`docs/methodology/survey-theory.md`) — formal justification for design-based variance estimation with modern DiD influence functions, citing Binder (1983), Rao & Wu (1988), Shao (1996)
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-**Research-grade survey DGP** — 8 new parameters on `generate_survey_did_data()`: `icc`, `weight_cv`, `informative_sampling`, `heterogeneous_te_by_strata`, `te_covariate_interaction`, `covariate_effects`, `strata_sizes`, `return_true_population_att`. All backward-compatible.
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-**R validation expansion** — 4 additional estimators cross-validated against R's `survey::svyglm()`: ImputationDiD, StackedDiD, SunAbraham, TripleDifference. Survey R validation coverage now 8 of 16 estimators.
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-**LinkedIn carousel** for Wooldridge ETWFE estimator announcement
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### Changed
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- Survey tutorial rewritten: leads with "Why Survey Design Matters" section showing flat-weight vs design-based comparison with known ground truth, coverage simulation, and false pre-trend detection rates
Copy file name to clipboardExpand all lines: docs/llms-full.txt
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> A Python library for Difference-in-Differences causal inference analysis. Provides sklearn-like estimators with statsmodels-style output for econometric analysis.
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