@gary_king
⚠️ Unofficial community showcase of Prof. Gary King's methods software (matching, missing data, and more). Not affiliated — all credit to the original authors; this summarizes public docs.
Workflows
Is your counterfactual an extrapolation? (WhatIf)
Flags when a counterfactual question is a safe interpolation versus a model-dependent extrapolation far from your data.
The balance–sample-size frontier (MatchingFrontier)
Trace the whole tradeoff curve between covariate balance and how many units you keep, then estimate the effect at every point on the frontier.
Simulation-based inference for any model (clarify)
Turn any fitted model into interpretable quantities of interest — average marginal effects, predictions, contrasts — with simulation-based confidence intervals.
Ecological inference (ei)
Infers individual-level behavior from aggregate (district-level) data, the classic example being voting rates by race from precinct totals.
Coarsened exact matching (CEM)
Temporarily coarsens each covariate into bins, exact-matches treated and controls within bins, then estimates effects on the matched data.
Multiple imputation of missing data (Amelia)
Fills in missing values via fast bootstrap-EM multiple imputation, producing several complete datasets you analyze and combine.
Matching for causal inference (MatchIt)
Preprocesses observational data by matching treated and control units on covariates, so downstream models depend less on modeling assumptions.