The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Estimation in Parallel Randomized Experiments
Abstract
Many studies comparing new treatments to standard treatments consist of parallel randomized experiments. In the example considered here, randomized experiments were conducted in eight schools to determine the effectiveness of special coaching programs for the SAT. The purpose here is to illustrate Bayesian and empirical Bayesian techniques that can be used to help summarize the evidence in such data about differences among treatments, thereby obtaining improved estimates of the treatment effect in each experiment, including the one having the largest observed effect. Three main tools are illustrated: 1) graphical techniques for displaying sensitivity within an empirical Bayes framework, 2) simple simulation techniques for generating Bayesian posterior distributions of individual effects and the largest effect, and 3) methods for monitoring the adequacy of the Bayesian model specification by simulating the posterior predictive distribution in hypothetical replications of the same treatments in the same eight schools.
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“The data are consistent with a standard deviation of 0, but it could also be as high as 10 or 20.”
From Analysis of variance—why it is more important than ever (2005) · cites this paper as Rubin (1981)
Citations
Cites
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Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; Vol. IV
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Estimation with Quadratic Loss
James, W., & Stein, C. (1992) · Springer Series in Statistics · doi:10.1007/978-1-4612-0919-5_30 · Cited by 2,252
Bayes Estimates for the Linear Model
Lindley, D. V., & Smith, A. F. M. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00885.x · Cited by 2,025
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Proceedings of the 6th Berkeley Symposium on Mathematical Statistics and Probability
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Cited by
(2015) · doi:10.1007/s11222-016-9696-4 · Cited by 5,611
The Handbook of Research Synthesis and Meta-Analysis
(2019) · doi:10.7758/9781610448864 · Cited by 4,553
Gelman, A. (2006) · Bayesian Analysis · doi:10.1214/06-ba117a · Cited by 4,050
Understanding predictive information criteria for Bayesian models
Gelman, A., Hwang, J., & Vehtari, A. (2014) · Statistics and Computing · doi:10.1007/s11222-013-9416-2 · Cited by 2,104
“From Rubin (1981).”
MethodInfluentialPOSTERIOR PREDICTIVE ASSESSMENT OF MODEL FITNESS VIA REALIZED DISCREPANCIES
Gelman, A., Meng, X., & Stern, H. S. (1996) · Cited by 1,945
Metadata
- Authors
- Rubin, D. B.
- Affiliations
- Educational Testing Service (US)
- Corresponding author
- Rubin, Donald B.
- ORCID
- Rubin, Donald B.
- Venue
- Journal of Educational Statistics
- Published
- 1981-12
- Volume
- 6
- Issue
- 4
- Pages
- 377-401
- ISSN
- 0362-9791 (ISSN-L)
- OpenAlex
- W2101756511
- Cited by
- 269
- References
- 19
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 19 · 2023: 6 · 2022: 12 · 2021: 8 · 2020: 17 · 2019: 10 · 2018: 8 · 2017: 13 · 2016: 13 · 2015: 10 · 2014: 9 · 2013: 7 · 2012: 3
- FWCI
- 0.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
- Locations
- Journal of Educational Statistics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- empirical Bayes, Bayesian estimation, treatment effect estimation, sensitivity analysis, posterior predictive distribution, model adequacy assessment, individual treatment effects
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Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Estimation in Parallel Randomized Experiments. https://app.cochat.ai/papers/10.3102/10769986006004377
- The paper
- Rubin, D. B. (1981). Estimation in Parallel Randomized Experiments. Journal of Educational Statistics. https://doi.org/10.3102/10769986006004377
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.
