115 citations · 122 across the 7 of their papers we have counts for
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Variance Estimation for Weighted Average Treatment Effects
Huiyue Li, Yi Liu, Yunji Zhou +3
Common variance estimation methods for weighted average treatment effects (WATEs) in observational studies include nonparametric bootstrap and model-based, closed-form sandwich var…
Average treatment effect on the treated, under lack of positivity
Yi Liu, Huiyue Li, Yunji Zhou +1
The use of propensity score (PS) methods has become ubiquitous in causal inference. At the heart of these methods is the positivity assumption. Violation of the positivity assumpti…
Overlap, matching, or entropy weights: what are we weighting for?
Roland A. Matsouaka, Yi Liu, Yunji Zhou
There has been a recent surge in statistical methods for handling the lack of adequate positivity when using inverse probability weights (IPW). However, these nascent developments…
Variance estimation for the average treatment effects on the treated and on the controls
Roland A. Matsouaka, Yi Liu, Yunji Zhou
Common causal estimands include the average treatment effect (ATE), the average treatment effect of the treated (ATT), and the average treatment effect on the controls (ATC). Using…
Constrained randomization and statistical inference for multi-arm parallel cluster randomized controlled trials
Yunji Zhou, Elizabeth L. Turner, Ryan A. Simmons +1
A practical limitation of cluster randomized controlled trials (cRCTs) is that the number of available clusters may be small, resulting in an increased risk of baseline imbalance u…
A framework for causal inference in the presence of extreme inverse probability weights: the role of overlap weights
Roland A. Matsouaka, Yunji Zhou
In this paper, we consider recent progress in estimating the average treatment effect when extreme inverse probability weights are present and focus on methods that account for a p…
Propensity score weighting under limited overlap and model misspecification
Yunji Zhou, Roland A. Matsouaka, Laine Thomas
Propensity score (PS) weighting methods are often used in non-randomized studies to adjust for confounding and assess treatment effects. The most popular among them, the inverse pr…