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1
Triggering-Effect Models for Multi-Type Recurrent Events and Biased Coin Randomization for Biomarker-Stratified Multiarm Trials
Triggering-Effect Models for Multi-Type Recurrent Events and Biased Coin Randomization for Biomarker-Stratified Multiarm Trials
Song, Tianhao. | The University of North Carolina at Chapel Hill | 2025
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2
Advancing Medication Development for Alcohol Use Disorder Using Randomized Clinical Trials
Advancing Medication Development for Alcohol Use Disorder Using Randomized Clinical Trials
Donato, Suzanna. | University of California, Los Angeles | 2025
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3
Design and Inference of Randomized Experiments for Modern Applications
Design and Inference of Randomized Experiments for Modern Applications
Wu, Yuhang. | University of California, Berkeley | 2025
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4
Design-Based Causal Inference for Randomized Experiments: A Unified Framework for a Diverging Number of Treatment Arms and Varying Sample Sizes
Design-Based Causal Inference for Randomized Experiments: A Unified Framework for a Diverging Number of Treatment Arms and Varying Sample Sizes
Shi, Lei. | University of California, Berkeley | 2025
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5
Fast Transforms for Gaussian Random Fields
Fast Transforms for Gaussian Random Fields
Beckman, Paul G. | New York University | 2025
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6
On Canonical Purification of Random Tensor Networks
On Canonical Purification of Random Tensor Networks
Lin, Simon. | University of Illinois at Urbana-Champaign | 2023
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7
Methods for Leveraging Secondary Endpoints in the Analysis of Randomized Trials
Methods for Leveraging Secondary Endpoints in the Analysis of Randomized Trials
Wolf, Jack Mathias. | University of Minnesota | 2025
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8
The Augmented Synthetic Control Method With Interference and Randomization-Based Covariance Analysis for Restricted Mean Survival Time Estimates
The Augmented Synthetic Control Method With Interference and Randomization-Based Covariance Analysis for Restricted Mean Survival Time Estimates
Krajewski, Taylor J. | The University of North Carolina at Chapel Hill | 2025
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9
Signal Detection with High-Dimensional Random Matrix Models
Signal Detection with High-Dimensional Random Matrix Models
Malinas, Robert P. | University of Michigan | 2025
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10
Random Covariance Models, Functional Brain Networks, and Interpretable Deep Learning for Multiomic Data Integration
Random Covariance Models, Functional Brain Networks, and Interpretable Deep Learning for Multiomic Data Integration
Neville, Quinton Daniel. | University of Minnesota | 2024
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