Image de couverture de livre

A Functional-Class Meta-Analytic Framework for Quantifying Surrogate Resilience

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Hsiao, Emily, Parast, Layla
Format:	Preprint
Publié:	2026
Sujets:	Methodology
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Resilience Measures for the Surrogate Paradox
par: Hsiao, Emily, et autres
Publié: (2025)

Assessing Surrogate Heterogeneity in Real World Data Using Meta-Learners
par: Knowlton, Rebecca, et autres
Publié: (2025)

Efficient Testing Using Surrogate Information
par: Knowlton, Rebecca, et autres
Publié: (2025)

A Bayesian Critique of Rank-Based Methods for Surrogate Marker Evaluation
par: Carlotti, Pietro, et autres
Publié: (2026)

Robust Evaluation of Longitudinal Surrogate Markers with Censored Data
par: Agniel, Denis, et autres
Publié: (2024)

Group Sequential Testing of a Treatment Effect Using a Surrogate Marker
par: Parast, Layla, et autres
Publié: (2024)

Meta-Analysis of High-Dimensional Surrogate Markers
par: Hughes, Arthur, et autres
Publié: (2026)

A Causal Framework for Evaluating Jointly Longitudinal Outcomes and Surrogate Markers: A State-Space Approach
par: Santos Jr., Silvaneo V. dos, et autres
Publié: (2026)

Model-free Approach to Evaluate a Censored Intermediate Outcome as a Surrogate for Overall Survival
par: Wang, Xuan, et autres
Publié: (2024)

Semiparametric Joint Modeling to Estimate the Treatment Effect on a Longitudinal Surrogate with Application to Chronic Kidney Disease Trials
par: Wang, Xuan, et autres
Publié: (2024)

Correcting for Missing Data When Evaluating Surrogate Markers in a Clinical Trial
par: Lotspeich, Sarah C., et autres
Publié: (2026)

RISE: Two-Stage Rank-Based Identification of High-Dimensional Surrogate Markers Applied to Vaccinology
par: Hughes, Arthur, et autres
Publié: (2025)

Bias in Meta-Analytic Modeling of Surrogate Endpoints in Cancer Screening Trials
par: Long, James P., et autres
Publié: (2025)

Efficient Testing Using Surrogate Information
par: Rebecca Knowlton, et autres
Publié: (2025)

A General Framework to Assess Complex Heterogeneity in the Strength of a Surrogate Marker
par: Rebecca Knowlton, et autres
Publié: (2025)

Evaluation of Surrogate Endpoints Based on Meta-Analysis with Surrogate Indices
par: Stijven, Florian, et autres
Publié: (2025)

A Bayesian Framework for Quantifying Association Between Functional and Structural Data in Neuroimaging
par: Mahat, Sakul, et autres
Publié: (2026)

An Online Meta-Level Adaptive Design Framework with Targeted Learning Inference: Applications to Evaluating and Utilizing Surrogate Outcomes in Adaptive Designs
par: Zhang, Wenxin, et autres
Publié: (2024)

Interpretable Deep Neural Network for Modeling Functional Surrogates
par: Jeon, Yeseul, et autres
Publié: (2025)

Precision of Treatment Hierarchy: A Metric for Quantifying Certainty in Treatment Hierarchies from Network Meta-Analysis
par: Wigle, Augustine, et autres
Publié: (2025)

Model Selection and Parameter Inference through Constraints via Sequences of Surrogate Smoothing Functions
par: Shaikh, Mateen R
Publié: (2026)

Nonstationary Gaussian Process Surrogates
par: Booth, Annie S., et autres
Publié: (2023)

Fast Meta-Analytic Approximations for Relational Event Models: Applications to Data Streams and Multilevel Data
par: Mulder, Fabio Vieira Roger Leenders Joris
Publié: (2023)

A Sensitivity Analysis Framework for Quantifying Confidence in Decisions in the Presence of Data Uncertainty
par: Wadekar, Adway S., et autres
Publié: (2025)

Surrogate-Assisted Targeted Learning for Nested Bridge Functionals under Administrative Censoring
par: Li, Lin, et autres
Publié: (2026)

Surrogate-Powered Inference: Regularization and Adaptivity
par: Chen, Jianmin, et autres
Publié: (2025)

Bayesian Optimization Sequential Surrogate (BOSS) Algorithm: Fast Bayesian Inference for a Broad Class of Bayesian Hierarchical Models
par: Li, Dayi, et autres
Publié: (2024)

A Surrogate Endpoint Based Provisional Approval Causal Roadmap
par: Gilbert, Peter B., et autres
Publié: (2024)

Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index
par: Athey, Susan, et autres
Publié: (2016)

Quantifying Time-Varying Physical Activity Intervention Effects via Functional Regression
par: Pai, Nidhi, et autres
Publié: (2026)

A Unified Hierarchical Multi-Task Multi-Fidelity Framework for Data-Efficient Surrogate Modeling in Manufacturing
par: Mehta, Manan, et autres
Publié: (2026)

Model‐Free Approach to Evaluate a Censored Intermediate Outcome as a Surrogate for Overall Survival
par: Xuan Wang, et autres
Publié: (2025)

SLOACI: Surrogate-Leveraged Online Adaptive Causal Inference
par: Fan, Yingying, et autres
Publié: (2025)

A New Framework for Bayesian Function Registration
par: Ma, Yijia, et autres
Publié: (2024)

SANVI: A Fast Spectral-Assisted Network Variational Inference Method with an Extended Surrogate Likelihood Function
par: Wu, Dingbo, et autres
Publié: (2025)

Inverse sampling intensity weighting for preferential sampling adjustment
par: Hsiao, Thomas W., et autres
Publié: (2025)

A Bayesian Nonparametric Approach for Clustering Functional Trajectories over Time
par: Liang, Mingrui, et autres
Publié: (2024)

Propagating Surrogate Uncertainty in Bayesian Inverse Problems
par: Roberts, Andrew Gerard, et autres
Publié: (2026)

EFECT: A Method to Quantify the Reproducibility of Stochastic Simulations
par: Sego, T. J., et autres
Publié: (2024)

Switching Models of Oscillatory Networks Greatly Improve Inference of Dynamic Functional Connectivity
par: Hsin, Wan-Chi, et autres
Publié: (2024)