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From the 1 of 7 linked papers with an AI index.

most citedTargeted Data Fusion for Region-Specific Survival Effects in the AMP HIV Prevention Trials

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

stat.ME2026

Towards Best Practices for Covariate Adjustment in Regulatory Trials: From Fixed to Data-Adaptive Approaches

Laura B. Balzer, Lei Nie, Issa J. Dahabreh +15

The paper discusses how to improve precision in randomized clinical trials by using covariate adjustment, comparing traditional fixed parametric methods with flexible data‑adaptive…

stat.ME20261 cited

Targeted Data Fusion for Region-Specific Survival Effects in the AMP HIV Prevention Trials

Yi Liu, Alexander W. Levis, Ke Zhu +3

The Antibody Mediated Prevention (AMP) trials opened a new scientific frontier by showing that passively administered monoclonal broadly neutralizing antibodies (bnAbs) could preve…

stat.ME2026

History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes

Yuyao Wang, Alexander W. Levis, Shu Yang +1

Existing conformal prediction methods for time-to-event outcomes leverage only baseline covariates, producing prediction intervals that are insufficiently informative to facilitate…

stat.ME2026

Considerations for the Integration of Randomized Controlled Trials and Real-World Data

Sky Qiu, Charles Barr, Lauren Dang +18

As clinical decision-making increasingly moves toward individualized and context-specific treatment recommendations, reliance on any single evidence source, randomized or observati…

stat.ME2026

Bounding causal effects with an unknown mixture of informative and non-informative missingness

Max Rubinstein, Denis Agniel, Larry Han +2

In experimental and observational data settings, researchers often have limited knowledge of the reasons for missing outcomes. To address this uncertainty, we propose bounds on cau…

stat.ME2025

COADVISE: Covariate Adjustment with Variable Selection in Randomized Controlled Trials

Yi Liu, Ke Zhu, Larry Han +1

Adjusting for covariates in randomized controlled trials can enhance the credibility and efficiency of treatment effect estimation. However, handling numerous covariates and their…