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Discussion of “Randomization: The forgotten component of the randomized clinical trial”

Rosenberger, Uschner, and Wang do an excellent job of describing approaches to hypothesis tests based on the randomization distribution and offer the view that population-based inferences are inappropriate. Figures 1 and 2 display the conceptual and methodological differences between the two approaches, differences that are analogous to the distinction between modeland design-based inferences in the survey context. The authors identify the three principal benefits of randomization: (1) protection against treatment assignment bias, (2) making treatment groups stochastically comparable on both measured and unmeasured confounders, and (3) providing a basis for inference. They claim, quite correctly, that “... rationale (3) is often forgotten, ignored, or left untaught.” and issue a call to action to bring it back into the mainstream. Dramatic increases in computing speed and innovative algorithms have considerably broadened the contexts in which randomization distribution–based tests and other inferences are available. The authors have made notable contributions; however, the scope of applicability is limited by several challenges in the modern clinical trials context, including