Abstract

Design quality guidelines typically recommend that multiple baseline designs include at least three demonstrations of effects. Despite its widespread adoption, this recommendation does not appear grounded in empirical evidence. The main purpose of our study was to address this issue by assessing Type I error rate and power in multiple baseline designs. First, we generated 10,000 multiple baseline graphs, applied the dual-criteria method to each tier, and computed Type I error rate and power for different number of tiers showing a clear change. Second, two raters categorized the tiers for 300 multiple baseline graphs to replicate our analyses using visual inspection. When multiple baseline designs had at least three tiers and two or more of these tiers showed a clear change, the Type I error rate remained adequate (< .05) while power also reached acceptable levels (> .80). In contrast, requiring all tiers to show a clear change resulted in overly stringent conclusions (i.e., unacceptably low power). Therefore, our results suggest that researchers and practitioners should carefully consider limitations in power when requiring all tiers of a multiple baseline design to show a clear change in their analyses.

Highlights

  • Design quality guidelines typically recommend that multiple baseline designs include at least three demonstrations of effects

  • In contrast with other single-case designs, the multiple baseline design does not require the withdrawal of the treatment or the establishment of a criterion to be gradually changed, which may explain its predominant use in singlecase research (Baer, Wolf, & Risley, 1968; Kratochwill & Levin, 2014)

  • Analyzing tiers individually indicated that the dual-criteria method produced a Type I error rate of .08 and a power of

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Summary

Introduction

Design quality guidelines typically recommend that multiple baseline designs include at least three demonstrations of effects. Our results suggest that researchers and practitioners should carefully consider limitations in power when requiring all tiers of a multiple baseline design to show a clear change in their analyses. Perspectives on Behavior Science (2020) 43:605–616 design to demonstrate experimental control (Gast & Ledford, 2018; Horner et al, 2005; Kratochwill et al, 2010). Among these designs, researchers have found that multiple baseline designs were the most frequently used (Coon & Rapp, 2018; Shadish & Sullivan, 2011; Smith, 2012). When the purpose of the study is to demonstrate experimental control, the experimenter should only introduce the independent variable in a tier when the previous tier (i.e., preceding AB comparison) shows a clear change

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