Invited Commentary: Comparing the Independent Segments Procedure With Group Sequential Designs

Psychological science would become more efficient if researchers implemented sequential designs where feasible. Miller and Ulrich (2020) propose an independent segments procedure where data can be analyzed at a prespecified number of equally spaced looks while controlling the Type I error rate. Such procedures already exist in the sequential analysis literature, and in this commentary, I reflect on whether psychologist should choose to adopt these existing procedures instead. I believe limitations in the independent segments procedure make it relatively unattractive. Being forced to stop for futility based on a bound not chosen to control Type II errors, or reject a smallest effect size of interest in an equivalence test, limits the inferences one can make. Having to use a prespecified number of equally spaced looks is logistically inconvenient. And not having the flexibility to choose α and β spending functions limits the possibility to design efficient studies based on the goal and limitations of the researcher. Recent software packages such as rpact (Wassmer & Pahlke, 2019) make sequential designs equally easy to perform as the independent segments procedure. While learning new statistical methods always takes time, I believe psychological scientists should start on a path that will not limit them in the flexibility and inferences their statistical procedure provides.