Causal Estimation
Causal Estimation is a methodological framework within the Potential Outcomes Framework that identifies and quantifies the causal effect of a treatment or intervention by comparing observed outcomes under different hypothetical treatment assignments, distinguishing it from predictive or associative methods through its focus on counterfactual reasoning and unbiased effect measurement.
1.1K
Publications
148.4K
Citations
2.2K
Authors
914
Institutions
Publications per year
2017–2026
462
Parents
1.1K
Statistics and Causal Inference
Paul W. Holland · Journal of the American Statistical Association · 1986 · 5.1K citations
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University of California, Berkeley, United States
29 publications · 1.7K citations
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Harvard University
Cambridge, United States
52 h-index
162 publications
68.4K citations

Harvard University Press
Cambridge, United States
33 h-index
54 publications
27.4K citations
University of California, Berkeley
Berkeley, United States
32 h-index
104 publications
7.9K citations

Johns Hopkins University
Baltimore, United States
28 h-index
56 publications
10.5K citations
Stanford University
Stanford, United States
25 h-index
57 publications
9.2K citations
University of California, Los Angeles
Los Angeles, United States
24 h-index
53 publications
3.1K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
24 h-index
47 publications
14.1K citations
Columbia University
New York, United States
22 h-index
44 publications
5K citations
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44 publications · 22.5K citations
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Repository · 69 publications · 2.3K citations
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31 publications · 4K citations
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AJE · 32 publications · 7K citations
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27 publications · 12.3K citations
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