Power and Sample Size: methods and applications

The first part of this talk introduces the concepts of power and sample size calculations such as alpha levels, test power, and minimum detectable effect size. First, we show  how to make several manual simple calculations and how to replicate these calculations using Stata's -power- suite of commands. Then, we show how to create tables and graphs for power, sample size, and minimum detectable effect sizes for a range of possible values, followed by a discussion of strategies for increasing statistical power. The second part of this talk demonstrates how to calculate power using simulation-based methods and show how to create your own custom power calculation programs that leverage Stata's -power- command to create custom tables and graphs. Examples will include the power simulation of simple tests, regression coefficients, and interactions term from a multilevel model. Along the way you will learn how to create simulated datasets, use Stata's -simulate- command, and how to write your own Stata commands using -program- and -syntax-.

Presenter

Chuck Huber is Director of Statistical Outreach at StataCorp and Adjunct Associate Professor of Biostatistics at the Texas A&M School of Public Health and at the New York University School of Global Public Health. In addition to working with Stata's team of software developers, he produces instructional videos for the Stata Youtube channel, writes blog entries, develops online NetCourses and gives talks about Stata at conferences and universities. Most of his current work is focused on statistical methods used by behavioral and health scientists. He has published in the areas of neurology, human and animal genetics, alcohol and drug abuse prevention, nutrition and birth defects. Dr Huber currently teaches survey sampling at NYU and introductory biostatistics at Texas A&M where he previously taught categorical data analysis, survey data analysis, and statistical genetics.