Covariate-Adaptive Optimization in Online Clinical Trials
DOI10.1287/OPRE.2018.1818zbMath1457.62335OpenAlexW2947517542WikidataQ120697922 ScholiaQ120697922MaRDI QIDQ5129185
Nikita Korolko, Alexander M. Weinstein, Dimitris J. Bertsimas
Publication date: 26 October 2020
Published in: Operations Research (Search for Journal in Brave)
Full work available at URL: https://semanticscholar.org/paper/725a2d0a269dcca8bf26e14e063aaa9d593ab5e9
clinical trialsrobust optimizationmixed integer optimizationstatistical poweronline allocationcovariate-adaptive randomization
Applications of statistics to biology and medical sciences; meta analysis (62P10) Optimal statistical designs (62K05) Sampling theory, sample surveys (62D05) Medical applications (general) (92C50)
Related Items (2)
Cites Work
- A finite selection model for experimental design of the health insurance study
- Rerandomization to improve covariate balance in experiments
- Handling covariates in the design of clinical trials
- Modeling survival data: extending the Cox model
- Agnostic notes on regression adjustments to experimental data: reexamining Freedman's critique
- Theory and Applications of Robust Optimization
- The covariate-adaptive biased coin design for balancing clinical trials in the presence of prognostic factors
- The Power of Optimization Over Randomization in Designing Experiments Involving Small Samples
- The central role of the propensity score in observational studies for causal effects
- Optimum biased coin designs for sequential clinical trials with prognostic factors
- Robust Solutions of Uncertain Quadratic and Conic-Quadratic Problems
- Matching on‐the‐fly: Sequential allocation with higher power and efficiency
- Forcing a sequential experiment to be balanced
- Optimal multivariate matching before randomization
This page was built for publication: Covariate-Adaptive Optimization in Online Clinical Trials
