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Power analysis for single-case designs: Computations for (AB)k designs.

Larry V Hedges1, William R Shadish2, Prathiba Natesan Batley3

  • 1Department of Statistics, Northwestern University, Evanston, IL, USA.

Behavior Research Methods
|October 12, 2022
PubMed
Summary
This summary is machine-generated.

Power analyses for single-case experimental designs (SCEDs) show that high statistical power is achievable. Key factors include effect size, number of subjects, and phase reversals, aligning with existing design standards.

Keywords:
ABAB designsPowerSingle case designsSingle case experimental designsType-I errorType-II error

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Area of Science:

  • Behavioral Science
  • Psychology
  • Education Research

Background:

  • Current single-case experimental design (SCED) standards prioritize validity.
  • Statistical power considerations are increasingly important for SCEDs.
  • Existing standards do not fully address statistical power needs.

Purpose of the Study:

  • To compute and derive statistical power for (AB)k designs common in SCEDs.
  • To identify key factors influencing statistical power in SCEDs.
  • To provide guidance on achieving adequate power in SCED research.

Main Methods:

  • Power computations were performed for (AB)k designs with multiple cases.
  • The impact of various factors (effect size, subjects, phase reversals, autocorrelation, time-points, intraclass correlation) on power was analyzed.
  • Software for power computation was developed and made available.

Main Results:

  • Effect size has the largest impact on power, followed by the number of subjects and phase reversals.
  • High power is associated with effect sizes ≥ 0.75, ≥ 3 subjects, and ≥ 1 set of phase reversals (k>1).
  • Autocorrelations, time-points per phase, and intraclass correlations have a smaller, non-negligible impact.

Conclusions:

  • Achieving adequate statistical power in SCEDs is feasible under reasonable conditions.
  • Findings align with current SCED standards regarding design complexity and number of subjects.
  • The study provides practical insights for researchers designing SCEDs to ensure sufficient statistical power.