18 citations · 87 across the 23 of their papers we have counts for
6 papers · 1 filter
Concise Summarization of Heterogeneous Treatment Effect Using Total Variation Regularized Regression
Alex Deng, Pengchuan Zhang, Shouyuan Chen +2
Randomized controlled experiment has long been accepted as the golden standard for establishing causal link and estimating causal effect in various scientific fields. Average treat…
Covariate adjustment in randomization-based causal inference for 2K factorial designs
Jiannan Lu
We develop finite-population asymptotic theory for covariate adjustment in randomization-based causal inference for 2K factorial designs. In particular, we confirm that both the un…
Continuous Monitoring of A/B Tests without Pain: Optional Stopping in Bayesian Testing
Alex Deng, Jiannan Lu, Shouyuan Chen
A/B testing is one of the most successful applications of statistical theory in modern Internet age. One problem of Null Hypothesis Statistical Testing (NHST), the backbone of A/B…
On Randomization-based and Regression-based Inferences for 2^K Factorial Designs
Jiannan Lu
We extend the randomization-based causal inference framework in Dasgupta et al. (2015) for general 2^K factorial designs, and demonstrate the equivalence between regression-based a…
Principal stratification analysis using principal scores
Peng Ding, Jiannan Lu
Practitioners are interested in not only the average causal effect of the treatment on the outcome but also the underlying causal mechanism in the presence of an intermediate varia…
Demystifying the Bias from Selective Inference: a Revisit to Dawid's Treatment Selection Problem
Jiannan Lu, Alex Deng
We extend the heuristic discussion in Senn (2008) on the bias from selective inference for the treatment selection problem (Dawid 1994), by deriving the closed-form expression for…