Randomization procedures in single‐case intervention research contexts: (Some of) “the rest of the story”

Abstract

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.

Meta‐analyses and effect sizes in applied behavior analysis: A review and discussion

“…We have reviewed current meta-analytic methods and advocate for their increased use in applied behavior analysis research and literature reviews. The perspective advanced herein is consistent with a larger movement toward incorporating newer quantitative tools and methods in behavior science and behavior analysis in general (Caron, 2019;Craig & Fisher, 2019;DeHart & Kaplan, 2019;Elliffe & Elliffe, 2019;Falligant et al, 2020;Franck et al, 2019;Friedel et al, 2019;Gilroy et al, 2020;Greene et al, 2017;Jacobs, 2019;Kaplan et al, 2019;Killeen, 2019;Kyonka, 2019;Lanovaz et al, 2020;Levin et al, 2019;Riley et al, 2019;Turgeon & Lanovaz, 2020;Villarreal et al, 2019;Young, 2019). To borrow a quote attributed to Galileo, mathematics is the language of science.…”

An Improved Two Independent-Samples Randomization Test for Single-Case AB-Type Intervention Designs: A 20-Year Journey

“…When properly implemented in a manner consistent with a study's design-randomization process, a randomization test yields statistical conclusions that are probabilistically valid (cf. Edgington, 1996;Levin, Kratochwill, & Ferron, 2019; and as will become apparent throughout this article).…”

Behavioral Self-Regulation: A Comparison of Goals and Self-Monitoring for High School Students With Disabilities

“…That is, as treatment started with several days of training, during which students were learning intervention procedures and not implementing them during their target class, we were unsure whether students would show any treatment effects. This method of randomly selecting start dates still allowed the possible demonstration of intervention effects at different points in time across participants while maintaining methodological rigor and enhancing internal validity (Levin et al, 2019). Incorporating randomization into single-case research designs enhances rigor and validity in the same way randomization enhances group designs: randomly assigning participants to treatment or control groups—or randomly assigning the transition from control (i.e., baseline) to treatment—eliminates the influence of extraneous variables on the dependent variable (Kratochwill & Levin, 2010; Levin et al, 2019).…”