activity
20172022
collaborators

5 papers

stat.ME2022

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…

stat.ME2020

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…

stat.ME2020

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…

stat.ME2020

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…

stat.AP2017

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…