A novel evaluation of optimality for randomized controlled trials

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.

KEYWORDS:

• Accrual
• American Indians
• community based participatory research
• longitudinal

Funding

Partial funding for all the authors, except the second, comes from a grant from the USA NIH, National Institute on Minority Health and Health Disparities (5P20MD004805).

Additional information

Funding

Partial funding for all the authors, except the second, comes from a grant from the USA NIH, National Institute on Minority Health and Health Disparities (5P20MD004805).