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Following up on articles recently published in this journal, the present contribution tells (some of) "the rest of the story" about the value of randomization in single-case intervention research investigations. Invoking principles of internal, statistical-conclusion, and external validity, we begin by emphasizing the critical distinction between design randomization and analysis randomization, along with the necessary correspondence between the two. Four different types of single-case design-and-analysis randomization are then discussed. The persistent negative influence of serially dependent single-case outcome observations is highlighted, accompanied by examples of inappropriate applications of parametric and nonparametric tests that have appeared in the literature. We conclude by presenting valid applications of single-case randomization procedures in various single-case intervention contexts, with specific reference to a freely available Excel-based software package that can be accessed to incorporate the present randomization schemes into a wide variety of single-case intervention designs and analyses.
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Levin et al. (2019) studied this question.
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