Using Single-Case Experiments to Support Evidence-Based Decisions: How Much Is Enough?

For practitioners, the use of single-case experimental designs (SCEDs) in the research literature raises an important question: How many single-case experiments are enough to have sufficient confidence that an intervention will be effective with an individual from a given population? Although standards have been proposed to address this question, current guidelines do not appear to be strongly grounded in theory or empirical research. The purpose of our article is to address this issue by presenting guidelines to facilitate evidence-based decisions by adopting a simple statistical approach to quantify the support for interventions that have been validated using SCEDs. Specifically, we propose the use of success rates as a supplement to support evidence-based decisions. The proposed methodology allows practitioners to aggregate the results from single-case experiments to estimate the probability that a given intervention will produce a successful outcome. We also discuss considerations and limitations associated with this approach.