2013/05/21 by Adam Kapelner, Abba Μ. Krieger, Kapelner, Adam +2
Mathematics · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Inference #Statistical Methods in Clinical Trials #stat.ME
paper · pdf · doi:10.48550/arxiv.1305.4981
20 pages, 1 algorithm, 2 figures, 8 tables
arxiv created 2013/05/21 · openalex publication_date 2013/05/21 · arxiv updated 2013/05/23 · openalex created_date 2022/10/04 · openalex updated_date 2026/07/28
We propose a dynamic allocation procedure that increases power and efficiency when measuring an average treatment effect in sequential randomized trials. Subjects arrive iteratively and are either randomized or paired via a matching criterion to a previously randomized subject and administered the alternate treatment. We develop estimators for the average treatment effect that combine information from both the matched pairs and unmatched subjects as well as an exact test. Simulations illustrate the method's higher efficiency and power over competing allocation procedures in both controlled scenarios and historical experimental data.