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Covariate Adjustment in Stratified Experiments
In the special case of matched pairs, for example, the regression including treatment, covariates, and pair fixed effects is asymptotically optimal.
Designing Representative and Balanced Experiments by Local Randomization
We give novel asymptotically exact inference methods for locally randomized selection and assignment, allowing experimenters to report smaller confidence intervals if they designed a representative experiment.
Blocked Clusterwise Regression
We give inference results for a k-means style estimator of our model and develop information criteria to jointly select the number clusters for each latent variable.
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