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Area of Science:

  • Behavioral Science
  • Single-Case Experimental Designs

Background:

  • Alternating treatments designs (ATDs) rapidly alternate conditions, with sequences often randomized.
  • Visual analysis compares data paths; quantitative options include visual structured criteria (VSC) and ALIV (Actual and Linearly Interpolated Values).

Purpose of the Study:

  • To compare the statistical performance of VSC, ALIV with randomization tests, and binomial tests for ATD data.
  • To provide recommendations for applied researchers analyzing ATD data.

Main Methods:

  • Simulated data representing ATDs with randomized block designs were used.
  • Type I error rates and statistical power were evaluated for VSC, ALIV, and binomial tests.

Main Results:

  • Both VSC and ALIV controlled Type I errors, with ALIV closer to the nominal 5%.
  • The binomial test was excessively liberal (high Type I error rate).
  • ALIV with a randomization test demonstrated superior statistical power compared to VSC.

Conclusions:

  • ALIV with a randomization test is recommended for applied researchers analyzing ATD data with randomized sequences.
  • Complementing visual analysis with ALIV provides robust quantitative insights.
  • An existing website was updated to include graphical and numerical results for these analyses.