Simulation-based Sample Size Calculations

Sample size planning and power analysis are essential to planning a new study, but complicated study designs, statistical methods, and real-world challenges can often require customized methods to plan appropriately. In many cases, there is no easy calculator to determine sample size or power. This workshop will introduce you to Monte Carlo simulation methods for sample size and power planning. You will learn how to set up an appropriate statistical model for your study, determine appropriate effect sizes, make informed decisions about the underlying assumptions you want to make (or not make), and use simulation to estimate sample sizes and power for your study. Examples including t-tests, chi-square tests, regression, ANOVA, and logistic regression will be explored using R. While not required, having experience with sample size and power calculations — see our Introduction to Sample Size Calculations workshop — as well as familiarity with linear models — see our Interpreting Linear Models:  Regression and ANOVA workshop — and logistic regression — see our Introduction to Logistic Regression workshop — are recommended. The methods in this workshop will prepare you for our Sample Size Calculations for Mixed Models workshop.