4 citations · 6 across the 4 of their papers we have counts for
9 papers · 1 filter
Does Rerandomization Help Beyond Covariate Adjustment? A Review and Guide for Theory and Practice
Antônio Carlos Herling Ribeiro Junior, Zach Branson
Rerandomization is a modern experimental design technique that repeatedly randomizes treatment assignments until covariates are deemed balanced between treatment groups. This enhan…
Calibrated sensitivity models
Alec McClean, Zach Branson, Edward H. Kennedy
In causal inference, sensitivity models assess how unmeasured confounders could alter causal analyses, but the sensitivity parameter -- which quantifies the degree of unmeasured co…
A Unified Framework for Rerandomization using Quadratic Forms
Kyle Schindl, Zach Branson
When designing a randomized experiment, one way to ensure treatment and control groups exhibit similar covariate distributions is to randomize treatment until some prespecified lev…
Causal Effect Estimation after Propensity Score Trimming with Continuous Treatments
Zach Branson, Edward H. Kennedy, Sivaraman Balakrishnan +1
Propensity score trimming, which discards subjects with propensity scores below a threshold, is a common way to address positivity violations that complicate causal effect estimati…
Incremental causal effects: an introduction and review
Matteo Bonvini, Alec McClean, Zach Branson +1
In this chapter, we review the class of causal effects based on incremental propensity scores interventions proposed by Kennedy [2019]. The aim of incremental propensity score inte…
Evaluating A Key Instrumental Variable Assumption Using Randomization Tests
Zach Branson, Luke Keele
Instrumental variable (IV) analyses are becoming common in health services research and epidemiology. Most IV analyses use naturally occurring instruments, such as distance to a ho…