The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Rerandomization to improve covariate balance in experiments
Open accessAbstract
Randomized experiments are the “gold standard” for estimating causal effects, yet often in practice, chance imbalances exist in covariate distributions between treatment groups. If covariate data are available before units are exposed to treatments, these chance imbalances can be mitigated by first checking covariate balance before the physical experiment takes place. Provided a precise definition of imbalance has been specified in advance, unbalanced randomizations can be discarded, followed by a rerandomization, and this process can continue until a randomization yielding balance according to the definition is achieved. By improving covariate balance, rerandomization provides more precise and trustworthy estimates of treatment effects.
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Cites
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Cited by
Understanding and misunderstanding randomized controlled trials
Deaton, A., & Cartwright, N. (2018) · Social Science & Medicine · doi:10.1016/j.socscimed.2017.12.005 · Cited by 1,841
General Forms of Finite Population Central Limit Theorems with Applications to Causal Inference
Li, X., & Ding, P. (2017) · Journal of the American Statistical Association · doi:10.1080/01621459.2017.1295865 · Cited by 167
Bauer, C. C. C., Caballero, C., Scherer, E., West, M. R., Mrazek, M. D., Phillips, D. T., Whitfield-Gabrieli, S., & Gabrieli, J. D. E. (2019) · Behavioral Neuroscience · doi:10.1037/bne0000337 · Cited by 85
Covariate-adjusted Fisher randomization tests for the average treatment effect
Zhao, A., & Ding, P. (2021) · Journal of Econometrics · doi:10.1016/j.jeconom.2021.04.007 · Cited by 40
Metadata
- Authors
- Morgan, K. L., & Rubin, D. B.
- Venue
- The Annals of Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 2012-04-01
- Volume
- 40
- Issue
- 2
- Pages
- 1263-1282
- ISSN
- 0090-5364 (ISSN-L)
- OpenAlex
- W2078409839
- Cited by
- 353
- References
- 61
- FWCI
- 7.49
- Type
- journal article
- Language
- en
- Open access
- green
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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.
