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Causal inference in network experiments: regression-based analysis and design-based properties
Although we focus on regression-based point estimators and standard errors, our theory holds under the design-based framework, which assumes that the randomness comes solely from the design of network experiments and allows for arbitrary misspecification of the regression models.
Inference under Covariate-Adaptive Randomization with Imperfect Compliance
We use this to propose strategies to minimize their asymptotic variance in a hypothetical RCT based on data from a pilot study.
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