A. Diamond
Statistics and Probability · with Abadie · 2006–2014
A researcher in the Science corpus: 4 papers; trusts 30 researchers and is trusted by 130 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 49 citations into it; #415 of 12,932 by trust here, #497 by citations
- Economics and Econometrics — 21 citations into it
- Sociology and Political Science — 11 citations into it; #11,976 of 22,756 by trust here, #16,211 by citations
- Artificial Intelligence — 10 citations into it
- Causal Inference & Discovery — 9 citations into it; #29 of 364 by trust here, #29 by citations
- Political Science and International Relations — 8 citations into it; #24 of 4,701 by trust here, #88 by citations
Whom A. Diamond trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alberto Abadie
- Donald B. Rubin
- Guido W. Imbens
- David Card
- Jeffrey A. Smith
- Daniel F McCaffrey
- Brian K. Lee
- James J. Heckman
- Basque Country
- Marianne Bertrand
Who trusts A. Diamond overall
- Bruno Ferman
- José R. Zubizarreta
- Jennifer L. Hill
- Nathan Kallus
- César Zucco Júnior
- Susan Athey
- Alberto Abadie
- Ufuk Akcigit
- Cynthia Rudin
- Guido W. Imbens
Papers from A. Diamond's perspective
Ordered by how strongly the researchers A. Diamond trusts endorse each paper. Same corpus, a different order for every researcher.
- The central role of the propensity score in observational studies for causal effects
- Statistics and Causal Inference
- [On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9.] Comment: Neyman (1923) and Causal Inference in Experiments and Observational Studies
- On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
- Large Sample Properties of Matching Estimators for Average Treatment Effects
- Observational Studies
- Propensity score estimation with boosted regression for evaluating causal effects in observational studies.
- Covariance Adjustment in Randomized Experiments and Observational Studies
- Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: the Case of Manpower Training
- Empirical Strategies in Labor Economics
Their papers
- Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program (2010) — 5,021 citations
- Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies (2006) — 1,089 citations
- Synth: An R Package for Synthetic Control Methods in Comparative Case Studies (2011) — 406 citations
- Comparative Politics and the Synthetic Control Method (2014)