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Controlling Bias in Observational Studies: A Review
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Citations
Cited by
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Austin, P. C. (2011) · Multivariate Behavioral Research · doi:10.1080/00273171.2011.568786 · Cited by 12,242
Estimating causal effects of treatments in randomized and nonrandomized studies
Rubin, D. B. (1974) · Journal of Educational Psychology · doi:10.1037/h0037350 · Cited by 9,436
“Recent work on methods of reducing bias in nonrandomized studies is summarized in Cochran and Rubin (1974).”
MethodMatching as an econometric evaluation estimator: Evidence from evaluating a job training programme
Heckman, J. J., Ichimura, H., & Todd, P. E. (1997) · The Review of Economic Studies · doi:10.2307/2971733 · Cited by 5,486
Matching Methods for Causal Inference: A Review and a Look Forward
Stuart, E. A. (2010) · Statistical Science · doi:10.1214/09-sts313 · Cited by 5,478
Metadata
- Authors
- Cochran, W. G.
- Venue
- Matched Sampling for Causal Effects
- Publisher
- Cambridge University Press
- Published
- 2006-09-04
- Pages
- 30-58
- OpenAlex
- W1506399260
- Cited by
- 958
- References
- 0
- FWCI
- 130.83
- Type
- book chapter
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- CoChat. (2026). Citation check: Controlling Bias in Observational Studies: A Review. https://app.cochat.ai/papers/10.1017/cbo9780511810725.005
- The paper
- Cochran, W. G. (2006). Controlling Bias in Observational Studies: A Review. Matched Sampling for Causal Effects. https://doi.org/10.1017/cbo9780511810725.005
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
