- A review of basic concepts of statistical power and effect size
- A simulation-based approach to power analysis
- An overview of how to implement simulations in various popular software programs.
- When information is limited and uncertainty is high
- Buffering power against inaccurate effect size estimates
- Strategies for optimizing power beyond increasing sample size.
Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
About the Instructor
Sean Lane is an assistant professor at Purdue University in the Department of Psychological Sciences. His substantive interests center on emotion regulation processes, their downstream effects on health and relationships, and how they differ between healthy and clinical subgroups. He also develops and applies new quantitative methods in the service of answering such questions. Most recently, he has been interested in developing flexible and robust power analysis tools that can be used to optimize the design of complex longitudinal studies. Sean received a Ph.D. in Psychology from New York University in 2013.
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