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Comparison of randomization-test procedures for single-case multiple-baseline designs.

Joel R Levin1, John M Ferron2, Boris S Gafurov3

  • 1a Department of Educational Psychology , University of Arizona , Tucson , AZ , USA.

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Summary
This summary is machine-generated.

This study evaluated randomization tests for single-case multiple-baseline studies. Two random start-point procedures, Koehler-Levin and restricted Marascuilo-Busk, showed superior power in detecting intervention effects.

Keywords:
Single-case multiple-baseline designsrandomization-test analysesscientifically credible methodologysimulation studies

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Area of Science:

  • Behavioral Science
  • Psychology
  • Research Methodology

Background:

  • Single-case experimental designs (SCEDs) are crucial for evaluating interventions.
  • Analyzing SCED data requires robust statistical methods, particularly randomization tests.
  • Multiple-baseline designs are common in SCEDs, necessitating specific analytical approaches.

Purpose of the Study:

  • To investigate the statistical properties of five randomization-test procedures for single-case multiple-baseline intervention studies.
  • To compare the Type I error rates and statistical power of procedures with fixed versus random intervention start points.
  • To identify the most effective procedures for detecting intervention effects in various design conditions.

Main Methods:

  • Conducted three simulation investigations to assess randomization-test procedures.
  • Examined two procedures with fixed intervention start points (Wampold-Worsham, Revusky).
  • Evaluated three procedures with randomly determined intervention start points (Koehler-Levin, modified Revusky, restricted Marascuilo-Busk).

Main Results:

  • All five tested randomization-test procedures maintained acceptable Type I error probabilities.
  • The Koehler-Levin and restricted Marascuilo-Busk procedures demonstrated higher statistical power in detecting immediate, abrupt intervention effects across most simulated conditions.
  • Performance varied based on design characteristics, including series lengths.

Conclusions:

  • Randomization tests are viable for analyzing single-case multiple-baseline studies, maintaining appropriate Type I error rates.
  • For detecting immediate intervention effects, the Koehler-Levin and restricted Marascuilo-Busk procedures are recommended due to their superior power.
  • In designs with unequal series lengths, the modified Revusky or restricted Marascuilo-Busk procedures are advised.