8 citations · 9 across the 5 of their papers we have counts for
5 papers
Accurate collection of reasons for treatment discontinuation to better define estimands in clinical trials
Yongming Qu, Robin D. White, Stephen J. Ruberg
Background: Reasons for treatment discontinuation are important not only to understand the benefit and risk profile of experimental treatments, but also to help choose appropriate…
Selection bias in the treatment effect for a principal stratum
Yongming Qu, Stephen J. Ruberg, Junxiang Luo +1
Estimation of treatment effect for principal strata has been studied for more than two decades. Existing research exclusively focuses on the estimation, but there is little researc…
Assessing the commonly used assumptions in estimating the principal causal effect in clinical trials
Yongming Qu, Ilya Lipkovich, Stephen J. Ruberg
In clinical trials, it is often of interest to understand the principal causal effect (PCE), the average treatment effect for a principal stratum (a subset of patients defined by t…
Estimating the treatment effect for adherers using multiple imputation
Junxiang Luo, Stephen J. Ruberg, Yongming Qu
Randomized controlled trials are considered the gold standard to evaluate the treatment effect (estimand) for efficacy and safety. According to the recent International Council on…
Implementation of Tripartite Estimands Using Adherence Causal Estimators Under the Causal Inference Framework
Yongming Qu, Junxiang Luo, Stephen J. Ruberg
Intercurrent events (ICEs) and missing values are inevitable in clinical trials of any size and duration, making it difficult to assess the treatment effect for all patients in ran…