On the External Validity of Single-Case Designs: A Bayesian Approach

When selecting interventions for students or clients, practitioners typically need to estimate the probability that it will lead to socially significant changes in behavior. One potential solution to address this issue involves computing the conditional probability of success given prior experience and the outcomes observed in the research literature. The purpose of the study was to use Bayesian inference, an approach that considers prior beliefs, to examine how research evidence combined with practical experience may be used to assess the external validity (i.e., generality across participants) of findings from single-case research. Our results present the mean posterior probability with the high-density intervals for practitioners with different levels of experience. Relying on more research evidence and on more practical experience to make decisions tends to improve success rate estimates. Given that research on the topic remains limited, we argue that our proposal should not be viewed as immutable, but rather as a starting point for spurring further discussion and research on the topic.