Saved in:
| Main Authors: | Kang, Myeongjong, Yi, Sangyoon |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.03863 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Jointly modeling multiple endpoints for efficient treatment effect estimation in randomized controlled trials
by: Wolf, Jack M., et al.
Published: (2025)
by: Wolf, Jack M., et al.
Published: (2025)
Rank-based estimators of global treatment effects for cluster randomized trials with multiple endpoints
by: Smith, E. Davies, et al.
Published: (2024)
by: Smith, E. Davies, et al.
Published: (2024)
Using shrinkage methods to estimate treatment effects in overlapping subgroups in randomized clinical trials with a time-to-event endpoint
by: Wolbers, Marcel, et al.
Published: (2024)
by: Wolbers, Marcel, et al.
Published: (2024)
A comparison of methods for designing hybrid type 2 cluster-randomized trials with continuous effectiveness and implementation endpoints
by: Owen, Melody, et al.
Published: (2025)
by: Owen, Melody, et al.
Published: (2025)
Sensitivity Analysis for False Discovery Rate Estimation with Published p-Values
by: Cao, Tianyu, et al.
Published: (2026)
by: Cao, Tianyu, et al.
Published: (2026)
Estimating treatment effects with competing intercurrent events in randomized controlled trials
by: Lu, Sizhu, et al.
Published: (2025)
by: Lu, Sizhu, et al.
Published: (2025)
A novel longitudinal rank-sum test for multiple primary endpoints in clinical trials: Applications to neurodegenerative disorders
by: Xu, Xiaoming, et al.
Published: (2024)
by: Xu, Xiaoming, et al.
Published: (2024)
Estimating causal effects of continuous-time dynamic treatments with unmeasured confounders
by: Zhu, Haiyan, et al.
Published: (2026)
by: Zhu, Haiyan, et al.
Published: (2026)
Assurance Methods for designing a clinical trial with a delayed treatment effect
by: Salsbury, James, et al.
Published: (2023)
by: Salsbury, James, et al.
Published: (2023)
Adaptive clinical trial design with delayed treatment effects using elicited prior distributions
by: Salsbury, James, et al.
Published: (2025)
by: Salsbury, James, et al.
Published: (2025)
Modern approaches for evaluating treatment effect heterogeneity from clinical trials and observational data
by: Lipkovich, Ilya, et al.
Published: (2023)
by: Lipkovich, Ilya, et al.
Published: (2023)
Analysis of cohort stepped wedge cluster-randomized trials with non-ignorable dropout via joint modeling
by: Gasparini, Alessandro, et al.
Published: (2024)
by: Gasparini, Alessandro, et al.
Published: (2024)
Estimating heterogeneous treatment effects with survival outcomes via a deep survival learner
by: Sun, Yuming, et al.
Published: (2026)
by: Sun, Yuming, et al.
Published: (2026)
CHIMA: a correlation-aware high-dimensional mediation analysis with its application to the living brain project study
by: Osarfo, Samuel, et al.
Published: (2025)
by: Osarfo, Samuel, et al.
Published: (2025)
An adaptive design for optimizing treatment assignment in randomized clinical trials
by: Zhang, Wei, et al.
Published: (2025)
by: Zhang, Wei, et al.
Published: (2025)
Inference of treatment effect and its regional modifiers using restricted mean survival time in multi-regional clinical trials
by: Hua, Kaiyuan, et al.
Published: (2024)
by: Hua, Kaiyuan, et al.
Published: (2024)
Power calculation for cross-sectional stepped wedge cluster randomized trials with a time-to-event endpoint
by: Baumann, Mary Ryan, et al.
Published: (2023)
by: Baumann, Mary Ryan, et al.
Published: (2023)
Developing a predictive signature for two trial endpoints using the cross-validated risk scores method
by: Cherlin, Svetlana, et al.
Published: (2020)
by: Cherlin, Svetlana, et al.
Published: (2020)
Estimating the average treatment effect in cluster-randomized trials with misclassified outcomes and non-random validation subsets
by: Isenberg, Dane, et al.
Published: (2025)
by: Isenberg, Dane, et al.
Published: (2025)
Multilevel functional distributional models with application to continuous glucose monitoring in diabetes clinical trials
by: Matabuena, Marcos, et al.
Published: (2024)
by: Matabuena, Marcos, et al.
Published: (2024)
Retrieved dropout imputation considering administrative study withdrawal
by: Liu, Rong, et al.
Published: (2024)
by: Liu, Rong, et al.
Published: (2024)
Making all pairwise comparisons in multi-arm clinical trials without control treatment
by: Burnett, Thomas, et al.
Published: (2024)
by: Burnett, Thomas, et al.
Published: (2024)
Principal stratification with continuous treatments and continuous post-treatment variables
by: Antonelli, Joseph, et al.
Published: (2023)
by: Antonelli, Joseph, et al.
Published: (2023)
Multivariate incremental effects for continuous treatments: Studying the health effects of environmental mixtures
by: Huang, Zhuochao, et al.
Published: (2026)
by: Huang, Zhuochao, et al.
Published: (2026)
Parameterising the effect of a continuous treatment using average derivative effects
by: Hines, Oliver J., et al.
Published: (2021)
by: Hines, Oliver J., et al.
Published: (2021)
A CV-TMLE global test approach to improve power in rare disease clinical studies with multiple-component endpoints
by: Zhou, Tianyue, et al.
Published: (2026)
by: Zhou, Tianyue, et al.
Published: (2026)
Estimation and inference of average treatment effects under heterogeneous additive treatment effect model
by: Lu, Xin, et al.
Published: (2024)
by: Lu, Xin, et al.
Published: (2024)
Covariate adjustment for linear models in estimating treatment effects in randomised clinical trials. Some useful theory to guide simulation
by: Senn, Stephen, et al.
Published: (2025)
by: Senn, Stephen, et al.
Published: (2025)
Estimating causal effects of functional treatments with modified functional treatment policies
by: Jiang, Ziren, et al.
Published: (2026)
by: Jiang, Ziren, et al.
Published: (2026)
A response-adaptive multi-arm design for continuous endpoints based on a weighted information measure
by: Caruso, Gianmarco, et al.
Published: (2024)
by: Caruso, Gianmarco, et al.
Published: (2024)
A class of nonparametric methods for evaluating the effect of continuous treatments on survival outcomes
by: Jin, Yutong, et al.
Published: (2024)
by: Jin, Yutong, et al.
Published: (2024)
Leveraging machine learning to estimate individualized treatment effects in cluster-randomized trials
by: Li, Changjun, et al.
Published: (2026)
by: Li, Changjun, et al.
Published: (2026)
Integrating tumor burden with survival outcome for treatment effect evaluation in oncology trials
by: Bhandari, Saurabh, et al.
Published: (2025)
by: Bhandari, Saurabh, et al.
Published: (2025)
Generalizing conditional average treatment effects from nested randomized trials to all trial-eligible individuals
by: Wen, Lan, et al.
Published: (2026)
by: Wen, Lan, et al.
Published: (2026)
Doubly robust average treatment effect estimation for survival data
by: Lee, Byeonghee, et al.
Published: (2025)
by: Lee, Byeonghee, et al.
Published: (2025)
Generalized win fraction regression for composite survival endpoints
by: Cao, Zhiqiang, et al.
Published: (2026)
by: Cao, Zhiqiang, et al.
Published: (2026)
Factors affecting power in stepped wedge trials when the treatment effect varies with time
by: Kenny, Avi, et al.
Published: (2025)
by: Kenny, Avi, et al.
Published: (2025)
A comparison of methods for estimating the average treatment effect on the treated for externally controlled trials
by: Wang, Huan, et al.
Published: (2024)
by: Wang, Huan, et al.
Published: (2024)
Assessing treatment efficacy for interval-censored endpoints using multistate semi-Markov models fit to multiple data streams
by: Morsomme, Raphael, et al.
Published: (2025)
by: Morsomme, Raphael, et al.
Published: (2025)
Performance of prior event rate ratio method in the presence of differential mortality or dropout
by: Cheung, Yin Bun, et al.
Published: (2025)
by: Cheung, Yin Bun, et al.
Published: (2025)
Similar Items
-
Jointly modeling multiple endpoints for efficient treatment effect estimation in randomized controlled trials
by: Wolf, Jack M., et al.
Published: (2025) -
Rank-based estimators of global treatment effects for cluster randomized trials with multiple endpoints
by: Smith, E. Davies, et al.
Published: (2024) -
Using shrinkage methods to estimate treatment effects in overlapping subgroups in randomized clinical trials with a time-to-event endpoint
by: Wolbers, Marcel, et al.
Published: (2024) -
A comparison of methods for designing hybrid type 2 cluster-randomized trials with continuous effectiveness and implementation endpoints
by: Owen, Melody, et al.
Published: (2025) -
Sensitivity Analysis for False Discovery Rate Estimation with Published p-Values
by: Cao, Tianyu, et al.
Published: (2026)