Vittorio Orlandi

Statistics and Probability · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 14 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 36 citations into it; #9,821 of 12,932 by trust here, #10,855 by citations
• Artificial Intelligence — 11 citations into it
• Causal Inference & Discovery — 10 citations into it
• Education — 9 citations into it
• Economics and Econometrics — 5 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Vittorio Orlandi trusts overall

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

1. Paul R. Rosenbaum
2. Donald B. Rubin
3. José R. Zubizarreta
4. Ben B. Hansen
5. R. Lalonde
6. Stefano Maria Iacus
7. Cynthia Rudin
8. Jennifer L. Hill
9. David W. Scott
10. Jerome H. Friedman

Who trusts Vittorio Orlandi overall

1. Sudeepa Roy
2. Cynthia Rudin

Papers from Vittorio Orlandi's perspective

Ordered by how strongly the researchers Vittorio Orlandi 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. Matching methods for causal inference: A review and a look forward
4. Evaluating the Econometric Evaluations of Training Programs with Experimental Data
5. Journal of the American Statistical Association Using Mixed Integer Programming for Matching in an Observational Study of Kidney Failure after Surgery Using Mixed Integer Programming for Matching in…
6. Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies
7. The prognostic analogue of the propensity score
8. Matching for Balance, Pairing for Heterogeneity in an Observational Study of the Effectiveness of For-Profit and Not-For-Profit High Schools in Chile
9. Matching using estimated propensity scores: relating theory to practice.
10. Optimal Full Matching and Related Designs via Network Flows

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