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Correction: Ferris et al. (2025) Chaining Differential Reinforcement of Compliance and Functional Communication Training to Treat Challenging Behavior Maintained by Negative Reinforcement. <i>Behavioral Sciences</i>, <i>15</i>(7), 891.

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Randomization tests as alternative analysis methods for behavior-analytic data.

Andrew R Craig1, Wayne W Fisher2

  • 1SUNY Upstate Medical University.

Journal of the Experimental Analysis of Behavior
|February 2, 2019
PubMed
Summary
This summary is machine-generated.

Randomization statistics provide flexible alternatives to traditional methods in behavior analysis. These powerful techniques are robust for small datasets and applicable across various research designs, including single-case studies.

Keywords:
autocorrelationbetween-groups researchdata analysisnonparametric statisticsrandomizationsingle-case researchwithin-subjects research

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Area of Science:

  • Behavior Analysis
  • Psychological Sciences

Background:

  • Traditional statistical methods in behavior analysis often rely on distributional assumptions.
  • Parametric and nonparametric techniques may not be optimal for all psychological research, especially with small sample sizes.

Purpose of the Study:

  • Introduce randomization statistics as a flexible alternative to conventional methods.
  • Highlight the suitability of randomization statistics for behavior-analytic data.
  • Provide a historical overview and practical considerations for applying randomization methods.

Main Methods:

  • Discuss the properties of randomization statistics.
  • Explain the underlying assumptions of randomization methods.
  • Demonstrate calculations for mixed and single-case research designs.

Main Results:

  • Randomization statistics offer flexibility without distributional assumptions.
  • These methods are robust for small-n datasets.
  • Applicable to between-groups, within-subjects, mixed, and single-case designs.

Conclusions:

  • Randomization statistics are a valuable tool for behavior analysis and psychological research.
  • These methods enhance data analysis flexibility and robustness.
  • Resources are provided for implementing randomization tests.