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August 2002 Covariance Adjustment in Randomized Experiments and Observational Studies
Paul R. Rosenbaum
Statist. Sci. 17(3): 286-327 (August 2002). DOI: 10.1214/ss/1042727942


By slightly reframing the concept of covariance adjustment in randomized experiments, a method of exact permutation inference is derived that is entirely free of distributional assumptions and uses the random assignment of treatments as the "reasoned basis for inference.'' This method of exact permutation inference may be used with many forms of covariance adjustment, including robust regression and locally weighted smoothers. The method is then generalized to observational studies where treatments were not randomly assigned, so that sensitivity to hidden biases must be examined. Adjustments using an instrumental variable are also discussed. The methods are illustrated using data from two observational studies.


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Paul R. Rosenbaum. "Covariance Adjustment in Randomized Experiments and Observational Studies." Statist. Sci. 17 (3) 286 - 327, August 2002.


Published: August 2002
First available in Project Euclid: 16 January 2003

zbMATH: 1013.62117
MathSciNet: MR1962487
Digital Object Identifier: 10.1214/ss/1042727942

Keywords: covariance adjustment , Matching , observational studies , permutation inference , propensity score , Randomization inference , sensitivity analysis

Rights: Copyright © 2002 Institute of Mathematical Statistics

Vol.17 • No. 3 • August 2002
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