A novel evaluation of optimality for randomized controlled trials. Issue 4 (4th July 2017)

• Record Type: Journal Article
• Authors: Wick, Jo; Berry, Scott M.; Yeh, Hung-Wen; Choi, Won; Pacheco, Christina M.; Daley, Christine; Gajewski, Byron J.
• Is Part Of: Journal of biopharmaceutical statistics. Volume 27:Issue 4(2017)
• Page Start: 659
• Page End: 672
• Publication Date: 2017-07-04
• Subjects: Accrual -- American Indians -- community based participatory research -- longitudinal; Pharmacy -- Statistical methods -- Periodicals; Drugs -- Testing -- Statistical methods -- Periodicals; Biometry -- Periodicals; Biopharmaceutics -- Periodicals; Pharmacokinetics -- Periodicals; 615.19
• DOI: 10.1080/10543406.2016.1198367
• Languages: English
• ISSNs: 1054-3406

Abstract

ABSTRACT: Balanced two-arm designs are more powerful than unbalanced designs and, consequently, Bayesian adaptive designs (BADs) are less powerful. However, when considering other subject- or community-focused design characteristics, fixed two-arm designs can be suboptimal. We use a novel approach to identify the best two-arm study design, taking into consideration both the statistical perspective and the community's perception. Data envelopment analysis (DEA) was used to estimate the relative performance of competing designs in the presence of multiple optimality criteria. The two-arm fixed design has enough deficiencies in subject- and community-specific benefit to make it the least favorable study design.