Factorial designs are widely used to study multiple treatments in one experiment. While t-
tests using a fully-saturated “long” model provide valid inferences,“short” model t-tests (that …

This article studies inference for the average treatment effect in randomized controlled trials
with covariate-adaptive randomization. Here, by covariate-adaptive randomization, we mean …

Randomized experiments have been the gold standard for assessing the effectiveness of a
treatment, policy, or intervention, spanning various fields, including social sciences …

In randomized controlled trials, treatment is often assigned by stratified randomization. I
show that among all stratified randomization schemes that treat all units with probability one …

Fisher's randomization test (frt) delivers exact p-values under the strong null hypothesis of
no treatment effect on any units whatsoever and allows for flexible covariate adjustment to …

The past two decades have witnessed a surge of new research in the analysis of
randomized experiments. The emergence of this literature may seem surprising given the …

Many websites now warehouse instructional materials designed to be taught by teachers in
a traditional classroom. What are the potential benefits of the new resources? We analyze …

In randomized clinical trials, adjustments for baseline covariates at both design and analysis
stages are highly encouraged by regulatory agencies. A recent trend is to use a model …

Inference for Cluster Randomized Experiments with Non-ignorable Cluster Sizes Page 1
Inference for Cluster Randomized Experiments with Non-ignorable Cluster Sizes Federico …

We consider the problem of estimating and inferring treatment effects in randomized
experiments. In practice, stratified randomization, or more generally, covariate-adaptive …