1 citations · 1 across the 1 of their papers we have counts for
5 papers
Deep Neural Networks Guided Ensemble Learning for Point Estimation
Tianyu Zhan, Haoda Fu, Jian Kang
In modern statistics, interests shift from pursuing the uniformly minimum variance unbiased estimator to reducing mean squared error (MSE) or residual squared error. Shrinkage base…
Deep Historical Borrowing Framework to Prospectively and Simultaneously Synthesize Control Information in Confirmatory Clinical Trials with Multiple Endpoints
Tianyu Zhan, Yiwang Zhou, Ziqian Geng +5
In current clinical trial development, historical information is receiving more attention as it provides utility beyond sample size calculation. Meta-analytic-predictive (MAP) prio…
A practical Response Adaptive Block Randomization (RABR) design with analytic type I error protection
Tianyu Zhan, Lu Cui, Ziqian Geng +3
Response adaptive randomization (RAR) is appealing from methodological, ethical, and pragmatic perspectives in the sense that subjects are more likely to be randomized to better pe…
Finite-Sample Two-Group Composite Hypothesis Testing via Machine Learning
Tianyu Zhan, Jian Kang
In the problem of composite hypothesis testing, identifying the potential uniformly most powerful (UMP) unbiased test is of great interest. Beyond typical hypothesis settings with…
Optimizing Graphical Procedures for Multiplicity Control in a Confirmatory Clinical Trial via Deep Learning
Tianyu Zhan, Alan H Hartford, Jian Kang +1
In confirmatory clinical trials, it has been proposed to use a simple iterative graphical approach to construct and perform intersection hypotheses tests with a weighted Bonferroni…