34 citations · 66 across the 18 of their papers we have counts for
18 papers
Empirical Simulation of Survival and Mixed-Type Data for Clinical Trial Design
Yao Chen, Jiren Sun, Yuxin Ding +2
Simulating realistic time-to-event data is essential for planning and evaluating complex clinical trial designs. Conventional approaches often sample event times from parametric fa…
Optimizing Efficiency and Convergence in MMRM: Practical Considerations for Longitudinal Data Analysis
Dylan Clarke, Jeremiah Jones, Yongming Qu
Mixed models for repeated measures (MMRM) are a popular method for analyzing longitudinal data in clinical trials. However, practical challenges, such as small sample sizes, large…
An Empirical Method for Analyzing Count Data
Jiren Sun, Linda Amoafo, Yongming Qu
Count endpoints are common in clinical trials, particularly for recurrent events such as hypoglycemia. When interest centers on comparing overall event rates between treatment grou…
Estimating treatment effects with competing intercurrent events in randomized controlled trials
Sizhu Lu, Yanyao Yi, Yongming Qu +3
The analysis of randomized controlled trials is often complicated by intercurrent events (IEs) -- events that occur after treatment initiation and affect either the interpretation…
Direct Estimation for Commonly Used Pattern-Mixture Models in Clinical Trials
Jitong Lou, Mallikarjuna Rettiganti, Yongming Qu
Pattern-mixture models have received increasing attention as they are commonly used to assess treatment effects in primary or sensitivity analyses for clinical trials with nonignor…
Retrieved dropout imputation considering administrative study withdrawal
Rong Liu, Yongming Qu
The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) E9 (R1) Addendum provides a framework for defining estimands in clinic…
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…
Using principal stratification in analysis of clinical trials
Ilya Lipkovich, Bohdana Ratitch, Yongming Qu +3
The ICH E9(R1) addendum (2019) proposed principal stratification (PS) as one of five strategies for dealing with intercurrent events. Therefore, understanding the strengths, limita…
Return-to-baseline multiple imputation for missing values in clinical trials
Yongming Qu, Biyue Dai
Return-to-baseline is an important method to impute missing values or unobserved potential outcomes when certain hypothetical strategies are used to handle intercurrent events in c…
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…
Analysis of an Incomplete Binary Outcome Dichotomized From an Underlying Continuous Variable in Clinical Trials
Chenchen Ma, Xin Shen, Yongming Qu +1
In many clinical trials, outcomes of interest include binary-valued endpoints. It is not uncommon that a binary-valued outcome is dichotomized from a continuous outcome at a thresh…
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 ICH E9 (R1): a few points learned during the COVID-19 pandemic
Yongming Qu, Ilya Lipkovich
The current COVID-19 pandemic poses numerous challenges for ongoing clinical trials and provides a stress-testing environment for the existing principles and practice of estimands…
Understanding and adjusting the selection bias from a proof-of-concept study to a more confirmatory study
Yongming Qu, Yu Du, Ying Zhang +1
It has long been noticed that the efficacy observed in small early phase studies is generally better than that observed in later larger studies. Historically, the inflation of the…
Defining Estimands Using a Mix of Strategies to Handle Intercurrent Events in Clinical Trials
Yongming Qu, Linda Shurzinske, Shanthi Sethuraman
Randomized controlled trials (RCT) are the gold standard for evaluation of the efficacy and safety of investigational interventions. If every patient in an RCT were to adhere to th…
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…
Estimation of group means in generalized linear mixed models
Jiexin Duan, Michael Levine, Junxiang Luo +1
In this manuscript, we investigate the concept of the mean response for a treatment group mean as well as its estimation and prediction for generalized linear models with a subject…