PoweR Analysis in Review: Leveraging R to Conduct Power Analyses for a Range of Research Designs

Area of Science:

• Statistical methodology
• Computational statistics

Background:

• Power analysis is crucial for research design but can be complex for sophisticated methods like longitudinal data analysis.
• Existing statistical software offers tools for power analysis, yet requires specific design and analytic decisions from researchers.

Purpose of the Study:

• To provide an overview of existing R packages for conducting power analyses.
• To introduce simulation-based approaches for power analysis in R, offering enhanced researcher control.

Main Methods:

• Review of current R packages for statistical power analysis.
• Demonstration of simulated power analyses using R, focusing on sample size determination.
• Utilizing R's free and open-source environment for advanced power analytic approaches.

Main Results:

• R offers a range of user-friendly tools for power analysis.
• Simulation methods in R provide researchers with maximum control over sample size determination.
• The R environment facilitates evolving power analytic strategies.

Conclusions:

• R is a versatile platform for conducting power analyses, accommodating both standard and advanced methodologies.
• Simulation-based power analysis in R is recommended for complex research designs requiring precise sample size control.
• Researchers with basic coding knowledge can leverage R for sophisticated power analysis, benefiting from its free and evolving ecosystem.