Marco Morucci

Statistics and Probability · 2018–2021

A researcher in the Science corpus: 5 papers; trusts 26 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 58 citations into it; #9,822 of 12,932 by trust here, #10,855 by citations
• Causal Inference & Discovery — 20 citations into it
• Artificial Intelligence — 14 citations into it
• Education — 11 citations into it
• Economics and Econometrics — 7 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Marco Morucci trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Donald B. Rubin
2. José R. Zubizarreta
3. Paul R. Rosenbaum
4. Ben B. Hansen
5. Alberto Abadie
6. Guido W. Imbens
7. Paul Holland
8. Stefano Maria Iacus
9. Gary King
10. R. Lalonde

Who trusts Marco Morucci overall

1. Sudeepa Roy
2. Cynthia Rudin
3. Alexander Volfovsky
4. Beau Coker
5. Awa Dieng
6. Vittorio Orlandi
7. Yameng Liu

Papers from Marco Morucci's perspective

Ordered by how strongly the researchers Marco Morucci trusts endorse each paper. Same corpus, a different order for every researcher.

1. The central role of the propensity score in observational studies for causal effects
2. Estimating causal effects of treatments in randomized and nonrandomized studies.
3. Statistics and Causal Inference
4. Evaluating the Econometric Evaluations of Training Programs with Experimental Data
5. Matching methods for causal inference: A review and a look forward
6. Large Sample Properties of Matching Estimators for Average Treatment Effects
7. Identification of Causal effects Using Instrumental Variables
8. Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies
9. For objective causal inference, design trumps analysis
10. [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

Their papers

• Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation (2020) — 16 citations
• Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference (2020) — 15 citations
• dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference (2021) — 4 citations
• Interpretable Almost Matching Exactly With Instrumental Variables (2019) — 5 citations
• Hypothesis Tests That Are Robust to Choice of Matching Method (2018) — 10 citations