A matching procedure for sequential experiments that iteratively learns which covariates improve power

DOI10.1111/biom.13561zbMath1522.62164arXiv2010.05980OpenAlexW3201384512MaRDI QIDQ6056148

Adam Kapelner, Abba M. Krieger

Publication date: 30 October 2023

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2010.05980

zbMATH Keywords

matchingclinical trialssequential experimentscovariate and response adaptive randomizationcrowdsourcing experimentation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (1)

Better experimental design by hybridizing binary matching with imbalance optimization

Cites Work

• Rerandomization to improve covariate balance in experiments
• Sequential monitoring with conditional randomization tests
• Handling covariates in the design of clinical trials
• Robust allocation schemes for clinical trials with prognostic factors
• Randomization in Clinical Trials
• Optimum biased coin designs for sequential clinical trials with prognostic factors
• Sequential rerandomization
• Harmonizing Optimized Designs With Classic Randomization in Experiments
• Matching on‐the‐fly: Sequential allocation with higher power and efficiency
• Causal Inference for Statistics, Social, and Biomedical Sciences
• Rerandomization to Balance Tiers of Covariates
• The Theory of Response‐Adaptive Randomization in Clinical Trials
• Forcing a sequential experiment to be balanced
• Optimal multivariate matching before randomization

This page was built for publication: A matching procedure for sequential experiments that iteratively learns which covariates improve power