Introduction to Sample Size Planning for Statistical Power

My goal is to give participants a motivating and interactive workshop experience that broadly considers sample size planning for confirmatory research studies. I aim to balance coverage of the conceptual foundations of sample size planning for statistical power with the practical execution of sample size planning in realistic conditions. The workshop is designed to provide a comprehensive introduction to sample size planning and provide researchers with the tools and knowledge to apply sample size planning in practice.

This workshop is designed for graduate students, post-doctoral fellows, faculty, and research scientists from the behavioral, social, educational, and health sciences and other related fields. It is recommended, but not required, that participants have a working knowledge of Analysis of Variance (ANOVA) and linear regression. Participants who would like a more thorough refresher on linear regression prior to attending may wish to watch our (no cost) Linear Regression Playlist on YouTube.

Chapter 1. General Introduction and Goals for Sample Size Planning
1.1. Introduction to Null Hypothesis Testing
1.2. Introduction to Effect Size Estimation
1.3. Benefits of Statistical Power

Chapter 2. Sample Size Planning for Statistical Power: Minimally Interesting Effect Size
2.1. Background and Definitions
2.2. Why Power Should be Considered A Priori, Not Post Hoc
2.3. Sample Size Planning Based on Minimally Interesting Effect Size
2.4. Sample Size Planning: MIES Approach in Practice

Chapter 3. Sample Size Planning for Statistical Power: Anticipated Effect Size
3.1. Issues When Using Prior Information as a Guide.
3.2. Sample Size Planning Based on Anticipated Effect Size
3.3. Sample Size Planning: BUCSS Approach in Practice

Chapter 4. Additional Considerations and Conclusions
4.1. Additional Considerations in Sample Size Planning for Power
4.2. Increasing Power Without Increasing Sample Size
4.3. Reporting, Software, and Conclusions

Chapter 5. Postscript: FAQ and Future Directions
5.1. Postscript: FAQ & Future Directions

Because each power analysis software package is best suited to a different type of sample size planning, specific software demonstrations will vary depending on the particular model and procedure used. Software demonstrations using the freely available program G*Power, freely available web applications, and the free statistical software R are interwoven with the lecture material. While it is helpful to have some familiarity with R ahead of time, this is not necessary. All necessary code, as well as screenshots of web application entries, are provided assuming no prior knowledge.

Participants receive lifetime access to all course materials, including complete course notes, lecture recordings, software demonstration notes, software demonstration recordings, and data and code for all examples. You can revisit these materials any time you like, without worrying about expiration dates. Pretty awesome, huh?

Content for this class is evergreen, meaning participants will always have access to the most current version of the course materials. Thus, if we replace a lecture recording or software demonstration, or update a syntax file, you will have immediate access to the updated content without needing to re-enroll in the class. Even more awesome.