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Tutorial: Small-N Power Analysis.

Elizabeth G E Kyonka1

  • 1Psychology, University of New England, Armidale, NSW 2351 Australia.

Perspectives on Behavior Science
|January 25, 2020
PubMed
Summary
This summary is machine-generated.

Power analysis is crucial for robust study design, estimating necessary sample sizes for reliable results. This tutorial guides behavior analysts in applying power analysis to various research designs, enhancing scientific rigor.

Keywords:
A priori power analysisEffect sizeExperimental designG*PowerHypothesis testingSample sizeTests of statistical significance

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Area of Science:

  • Behavior Analysis
  • Research Methodology
  • Statistical Power

Background:

  • Power analysis is often overlooked in study design.
  • A priori power analysis estimates sample size based on error rates and minimum meaningful effect size.
  • While common in large-group designs, power analysis is also vital for small-N and within-subjects research.

Purpose of the Study:

  • To highlight the importance of power analysis in behavior analysis research.
  • To demonstrate the application of power analysis in small-N and within-subjects designs.
  • To equip readers with the skills to conduct power analyses for their studies.

Main Methods:

  • Illustrates power analysis through case studies relevant to behavior analysts.
  • Explains how to estimate just noticeable differences from means and standard deviations.
  • Details converting these differences into standardized effect sizes.
  • Introduces the use of G*Power software for sample size determination.

Main Results:

  • Readers will gain the ability to perform a priori power analyses.
  • Case studies demonstrate practical applications in comparing groups and conditions.
  • The tutorial provides a clear pathway to determining adequate sample sizes for detecting meaningful effects.

Conclusions:

  • Power analysis is an essential tool for maximizing the probative value of research in behavior analysis.
  • Implementing power analysis ensures studies are adequately powered to detect meaningful effects.
  • This tutorial empowers behavior analysts to enhance the rigor and reliability of their research designs.