12 citations · 41 across the 11 of their papers we have counts for
6 papers · 1 filter
Rerandomization in Factorial Experiments
Xinran Li, Peng Ding, Donald B. Rubin
With many pretreatment covariates and treatment factors, the classical factorial experiment often fails to balance covariates across multiple factorial effects simultaneously. Ther…
Randomization Tests for Weak Null Hypotheses in Randomized Experiments
Jason Wu, Peng Ding
The Fisher randomization test (FRT) is appropriate for any test statistic, under a sharp null hypothesis that can recover all missing potential outcomes. However, it is often sough…
Randomization Inference for Peer Effects
Xinran Li, Peng Ding, Qian Lin +2
Many previous causal inference studies require no interference, that is, the potential outcomes of a unit do not depend on the treatments of other units. However, this no-interfere…
Regression adjustment in completely randomized experiments with a diverging number of covariates
Lihua Lei, Peng Ding
Randomized experiments have become important tools in empirical research. In a completely randomized treatment-control experiment, the simple difference in means of the outcome is…
Using Survival Information in Truncation by Death Problems Without the Monotonicity Assumption
Fan Yang, Peng Ding
In some randomized clinical trials, patients may die before the measurements of their outcomes. Even though randomization generates comparable treatment and control groups, the rem…
Causal Inference: A Missing Data Perspective
Peng Ding, Fan Li
Inferring causal effects of treatments is a central goal in many disciplines. The potential outcomes framework is a main statistical approach to causal inference, in which a causal…