Optimal allocation of sample size for randomization-based inference from 2K factorial designs

Optimizing the allocation of units into treatment groups can help researchers improve the precision of causal estimators and decrease costs when running factorial experiments. However, existing optimal allocation results typically assume a super-population model and that the outcome data come from a...

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Bibliographic Details

Published in:	Journal of Causal Inference
Main Authors:	Ravichandran Arun, Pashley Nicole E., Libgober Brian, Dasgupta Tirthankar
Format:	Article
Language:	English
Published:	De Gruyter 2024-02-01
Subjects:	randomization factorial design optimum allocation neyman 62k05 62k10 62k15 62d99
Online Access:	https://doi.org/10.1515/jci-2023-0046