Welcome to the Peer-to-Peer Teaching Spring Season 2025. These sessions are taught by your colleagues to fill our knowledge gaps and keep up with the accelerated pace at which bioinformatics grows as well as other data analysis methodologies. 

This session is dedicated to understanding how to be aware of your study power, and will be led by our colleague Shubham Misra, PhD who is a Postdoctoral Associate in the Department of Neurology.

Summary

Determining an appropriate sample size is a critical step in designing observational studies to ensure statistical power and validity. Proper sample size calculation minimizes bias, optimizes resource use, and enhances the reliability of study findings. R, a powerful statistical computing environment, provides various packages that facilitate sample size estimation for different study designs.

In this session, we will use R packages such as “pwr” to perform sample size calculations tailored to observational studies in clinical and pre-clinical settings. We will explore key concepts, including power analysis, effect size determination, and confidence interval estimation, to guide study design decisions.

You will learn how to:

• Understand the importance of sample size calculation in observational studies.

• Use R functions to calculate sample sizes for different study designs (e.g., cross-sectional, case-control, and cohort studies).

• Perform power analysis to assess study feasibility.

• Interpret and visualize sample size calculations.

Requirements:

• Basic knowledge of R and statistical concepts (e.g., hypothesis testing, confidence intervals).

• A laptop with the latest version of R and RStudio installed.

• Prework documentation with introductory materials and example datasets will be provided before the session.