The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
On regression adjustments in experiments with several treatments
Open accessAbstract
Regression adjustments are often made to experimental data. Since randomization does not justify the models, bias is likely; nor are the usual variance calculations to be trusted. Here, we evaluate regression adjustments using Neyman’s nonparametric model. Previous results are generalized, and more intuitive proofs are given. A bias term is isolated, and conditions are given for unbiased estimation in finite samples.
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Writing Group for the Women's Health Initiative Investigators (2002) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.288.3.321 · Cited by 15,889
Cook, N. R., Cutler, J. A., Obarzanek, E., Buring, J. E., Rexrode, K. M., Kumanyika, S. K., Appel, L. J., & Whelton, P. K. (2007) · BMJ · doi:10.1136/bmj.39147.604896.55 · Cited by 1,179
Evidence-Based Public Health: Moving Beyond Randomized Trials
Victora, C. G., Habicht, J.-P., & Bryce, J. (2004) · American Journal of Public Health · doi:10.2105/ajph.94.3.400 · Cited by 1,056
Gertler, P. (2004) · American Economic Review · doi:10.1257/0002828041302109 · Cited by 703
On regression adjustments to experimental data
Freedman, D. A. (2008) · Advances in Applied Mathematics · doi:10.1016/j.aam.2006.12.003 · Cited by 417
Self-citation
Cited by
In Pursuit of Balance: Randomization in Practice in Development Field Experiments
Bruhn, M., & McKenzie, D. (2009) · American Economic Journal: Applied Economics · doi:10.1257/app.1.4.200 · Cited by 788
Regression Discontinuity Designs Using Covariates
Calonico, S., Cattaneo, M. D., Farrell, M. H., & Titiunik, R. (2019) · The Review of Economics and Statistics · doi:10.1162/rest_a_00760 · Cited by 678
Gomila, R. (2021) · Journal of Experimental Psychology: General · doi:10.1037/xge0000920 · Cited by 561
Quantile Regression: 40 Years On
Koenker, R. (2017) · Annual Review of Economics · doi:10.1146/annurev-economics-063016-103651 · Cited by 331
Lasso adjustments of treatment effect estimates in randomized experiments
Bloniarz, A., Liu, H., Zhang, C.-H., Sekhon, J. S., & Yu, B. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510506113 · Cited by 169
Metadata
- Authors
- Freedman, D. A.
- Venue
- The Annals of Applied Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 2008-03-01
- Volume
- 2
- Issue
- 1
- Pages
- 176-196
- ISSN
- 1932-6157 (ISSN-L)
- OpenAlex
- W2047354426
- Cited by
- 177
- References
- 5
- FWCI
- 6.83
- Type
- journal article
- Language
- en
- Open access
- bronze
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