Juan David Correa

Statistics and Probability · 2017–2022

A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 33 citations into it; #7,512 of 12,932 by trust here, #7,914 by citations
• Artificial Intelligence — 30 citations into it; #32,143 of 35,345 by trust here, #29,412 by citations
• Causal Inference & Discovery — 24 citations into it
• Probabilistic & Bayesian Methods — 11 citations into it

Whom Juan David Correa trusts overall

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

1. Judea Pearl
2. Elias Bareinboim
3. Donald B. Rubin
4. Peter M. Bentler
5. Jin Tian
6. Tom L. Burr
7. James M. Robins
8. James J. Heckman
9. Bianca Zadrozny
10. J. Lunceford

Who trusts Juan David Correa overall

1. Jin Tian
2. Elias Bareinboim
3. Curriculum Vitae
4. Adarsh Subbaswamy
5. Irina Degtiar

Papers from Juan David Correa's perspective

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

1. Causality : Models , Reasoning , and Inference
2. Estimating causal effects of treatments in randomized and nonrandomized studies.
3. Causation, Prediction, and Search
4. Statistical Analysis With Missing Data
5. Sample selection bias as a specification error
6. The central role of the propensity score in observational studies for causal effects
7. [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
8. Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models
9. On the Testable Implications of Causal Models with Hidden Variables
10. Generalizing evidence from randomized clinical trials to target populations: The ACTG 320 trial.

Their papers

• Generalized Adjustment Under Confounding and Selection Biases (2018) — 60 citations
• Causal Effect Identification by Adjustment under Confounding and Selection Biases (2017) — 46 citations
• On Pearl’s Hierarchy and the Foundations of Causal Inference (2022) — 346 citations
• Adjustment Criteria for Generalizing Experimental Findings (2019) — 15 citations