9 citations · 21 across the 9 of their papers we have counts for
6 papers · 1 filter
tteICE: An R Package for Estimating Treatment Effects on Time-to-Event Outcomes with Intercurrent Events in Two-Arm Trials
Yuhao Deng, Yi Zhou, Yi Wang +1
Evaluating treatment effects in clinical trials with time-to-event outcomes is complicated by intercurrent events (ICEs), e.g., treatment discontinuation or competing events. While…
Estimating Pathway Treatment Effects in the Presence of Intermediate Events with Multi-State Data
Yuhao Deng, Haoyu Wei, Donglin Zeng +2
During clinical trials evaluating a drug's effect on a survival endpoint, intermediate events often occur in addition to the primary event. The treatment can exert its effect on th…
Inference for Cumulative Incidences and Treatment Effects in Randomized Controlled Trials with Time-to-Event Outcomes under ICH E9 (R1)
Yuhao Deng, Shasha Han, Xiao-Hua Zhou
In randomized controlled trials (RCTs) that focus on time-to-event outcomes, intercurrent events can arise in two ways: as semi-competing events, which modify the hazard of the pri…
Direct and Indirect Treatment Effects in the Presence of Semi-Competing Risks
Yuhao Deng, Yi Wang, Xiao-Hua Zhou
Semi-competing risks refer to the phenomenon that the terminal event (such as death) can censor the non-terminal event (such as disease progression) but not vice versa. The treatme…
Separable pathway effects of semi-competing risks using multi-state models
Yuhao Deng, Yi Wang, Xiang Zhan +1
Semi-competing risks refer to the phenomenon where a primary event (such as mortality) can ``censor'' an intermediate event (such as relapse of a disease), but not vice versa. Unde…
Causal Inference with Truncation-by-Death and Unmeasured Confounding
Yuhao Deng, Yingjun Chang, Xiao-Hua Zhou
Clinical studies sometimes encounter truncation by death, rendering outcomes undefined. Statistical analysis based solely on observed survivors may give biased results because the…