115 citations · 121 across the 8 of their papers we have counts for
8 papers
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…
Robust statistical inference for the matched net benefit and the matched win ratio using prioritized composite endpoints
Roland A. Matsouaka, Adrian Coles
As alternatives to the time-to-first-event analysis of composite endpoints, the {\it net benefit} (NB) and the {\it win ratio} (WR) -- which assess treatment effects using prioriti…
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…
Regression with a right-censored predictor, using inverse probability weighting methods
Roland A. Matsouaka, Folefac D. Atem
In a longitudinal study, measures of key variables might be incomplete or partially recorded due to drop-out, loss to follow-up, or early termination of the study occurring before…
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…
Linear regression model with a randomly censored predictor:Estimation procedures
Folefac Atem, Roland A. Matsouaka
We consider linear regression model estimation where the covariate of interest is randomly censored. Under a non-informative censoring mechanism, one may obtain valid estimates by…