Abstract
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.
Original language | English |
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Pages (from-to) | 498-500 |
Number of pages | 3 |
Journal | Psychological Methods |
Volume | 26 |
Issue number | 4 |
DOIs | |
Publication status | Published - Aug 2021 |
Funding
This work was funded by VIDI Grant 452-17-013 from the Netherlands Organization for Scientific Research.
Keywords
- hypothesis testing
- research efficiency
- sequential sampling
- Humans
- Research Design