Overview

In this workshop, we will provide a brief review of the concepts underlying power and sample size analysis. Following this, we will use R for hands-on programming practice with power and sample size calculations for several different types of analyses, including parametric and nonparametric tests using both analytical and simulation approaches.

Learning Objectives

• Become familiar with concepts such as type I and II error, effect sizes, and confidence intervals
• Know how to do power and sample size calculations for several common study designs and tests
• Know how to create power and sample size plots from grid searches
• Know how to use simulations for more complex analyses

Prerequisites

A basic understanding of statistics and the purpose of doing power and sample size calculations, and familiarity with R programming will be helpful but not required.

Software

If you want to follow the R coding exercises presented during this workshop, please install R and RStudio beforehand.

   Install R
   Install RStudio

Materials

Workshop materials will be available online here by the time the workshop begins, and will be available afterwards.

Instructors

Alan Paciorek is a Biostatistician and a Programmer Analyst at the Helen Diller Family Comprehensive Cancer Center and the Dept. of Epidemiology & Biostatistics

Karla Lindquist is the Scientific Lead for the Library's Data Science Initiative