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Related Concept Videos

Experimental Designs01:16

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An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
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A Within-Subject Experimental Design using an Object Location Task in Rats
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ABkPowerCalculator: An App to Compute Power for Balanced (AB)k Single Case Experimental Designs.

Prathiba Batley1, Madhav Thamaran2, Larry V Hedges3

  • 1Daiichi Sankyo, Inc.

Multivariate Behavioral Research
|October 17, 2023
PubMed
Summary
This summary is machine-generated.

Researchers can now easily calculate statistical power for single-case experimental designs using a new (AB)k power calculator. This accessible tool helps ensure studies have sufficient power to detect meaningful effects.

Keywords:
Single case experimental designseffect sizepower analysissingle case designssoftware

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Area of Science:

  • Behavioral Science
  • Medical Research
  • Psychology

Background:

  • Single-case experimental designs (SCEDs) are crucial in behavioral and medical research.
  • Existing SCED standards lack statistically derived power computations.
  • Applied researchers need accessible tools for power analysis in SCEDs.

Purpose of the Study:

  • To introduce a user-friendly Shiny App for calculating statistical power in balanced (AB)k designs.
  • To explain the derivation of power computations for (AB)k designs.
  • To provide an accessible tool for researchers without requiring software training.

Main Methods:

  • Development of a Shiny App implementing power computation equations for (AB)k designs.
  • The app supports power calculations for analyses involving multilevel models with autocorrelations.
  • The tool is designed for ease of use on various devices, including mobile phones.

Main Results:

  • The developed Shiny App provides accessible power computations for (AB)k designs.
  • The calculator requires no prior R programming knowledge.
  • The app is functional across different devices without needing R installation.

Conclusions:

  • The (AB)k power calculator Shiny App is a valuable resource for practitioners and applied researchers.
  • It facilitates the planning of single-case studies with adequate statistical power.
  • Enhances the rigor of behavioral and medical research utilizing SCEDs.