Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests

Brian Liu, Rahul Mazumder

We study the often overlooked phenomenon, first noted in Breiman (2001), that random forests appear to reduce bias compared to bagging. Motivated by a...

Fast Approximation of Shapley Values through Fractional Factorial Designs

Zheng Zhou, Robert Mee, Herbert Hamers et al.

A More Robust Approach to Multivariable Mendelian Randomization

Yinxiang Wu, others

Abstract

Design-Based Causal Inference with Missing Outcomes: Missingness Mechanisms, Imputation-Assisted Randomization Tests, and Covariate Adjustment

Siyu Heng, Yang Feng, Jiawei Zhang

Orthogonalized moment aberration for mixed-level multi-stratum factorial designs with partially-relaxed orthogonal block structures

Ming-Chung Chang

A Bayesian Criterion for Rerandomization

Zhaoyang Liu, Tingxuan Han, Donald B. Rubin et al.