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Optimal planning of adaptive two‐stage designs
Author(s) -
Pilz Maximilian,
Kunzmann Kevin,
Herrmann Carolin,
Rauch Geraldine,
Kieser Meinhard
Publication year - 2021
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.8953
Subject(s) - optimal design , computer science , adaptive design , sample size determination , mathematical optimization , adaptive strategies , clinical trial , machine learning , mathematics , statistics , medicine , archaeology , pathology , history
Adaptive designs are playing an increasingly important role in the planning of clinical trials. While there exists various research on the optimal determination of a two‐stage design, non‐optimal versions still are frequently applied in clinical research. In this article, we strive to motivate the application of optimal adaptive designs and give guidance on how to determine them. It is demonstrated that optimizing a trial design with respect to particular objective criteria can have a substantial benefit over the application of conventional adaptive sample size recalculation rules. Furthermore, we show that in many practical situations, optimal group‐sequential designs show an almost negligible performance loss compared to optimal adaptive designs. Finally, we illustrate how optimal designs can be tailored to specific operational requirements by customizing the underlying optimization problem.