@article{lakens_invited_2021-1,
	title = {Invited {Commentary}: {Comparing} the {Independent} {Segments} {Procedure} with {Group} {Sequential} {Designs}},
	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 1 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 procedure 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 2 errors,
or reject a smallest effect size of interest in an equivalence test, limit 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 limit 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.},
	journal = {Psychological Methods},
	author = {Lakens, Daniël},
	year = {2021},
}

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