In this series, I explain the basics of power analysis and how to use it to calculate the sample size needed for a study.

The videos focus on the procedure to perform power analysis and sample size calculation in jamovi and particularly in R, using the packages pwr (for simple designs) and Superpower (for more complex factorial designs). The section dedicated to pwr is largely based on this video by Daniel S. Quintana (2019).

This series is also supported by a practical guide:

1. Introduction

Basic concepts.

Sections:

1. Intro: (0:00)
2. Supporting document: (0:48)
3. Basic concepts: (2:11)
4. How to estimate the effect size: (5:14)
5. Common techniques and their limitations: (6:00)
6. Alternatives: (10:17)
7. Conclusions: (12:12)

Papers cited in this video:

Albers, C., & Lakens, D. (2018). When Power Analyses Based on Pilot Data Are Biased: Inaccurate Effect Size Estimators and Follow-up Bias. Journal of Experimental Social Psychology, 74, 187-195. https://doi.org/10.1016/j.jesp.2017.09.004

Correll, J., Mellinger, C., McClelland, G. H., & Judd, C. M. (2020). Avoid Cohen’s “Small”, “Medium”, and “Large” for Power Analysis. Trends in Cognitive Sciences, 24(3), 200-207. https://doi.org/10.1016/j.tics.2019.12.009

Lakens, D., Scheel, A. M., & Isager, P. M. (2018). Equivalence Testing for Psychological Research: A Tutorial. Advances in Methods and Practices in Psychological Science, 1(2), 259-269. https://doi.org/10.1177/2515245918770963

Quintana, D. S. (2017). Statistical Considerations for Reporting and Planning Heart Rate Variability Case-Control Studies. Psychophysiology, 54(3), 344-349. https://doi.org/10.1111/psyp.12798

2. Part 1 [Tutorial]

Simple designs: Corrleation, t-tests, one-way ANOVA

Sections:

1. Presentation: (0:00)
2. Intro to jpower for jamovi: (1:12)
   • 2.1 Installing jpower: (3:03)
   • 2.2 t-test type designs injpower: (3:41)
3. Intro to pwr¹ for R: (13:03)
   • 3.1 Small intro to R and RStudio: (13:44)
   • 3.2 Installing and loading pwr: (18:26)
   • 3.3 Correlations in pwr: (21:58)
   • 3.4 t-test type designs in pwr: (30:11)
   • 3.5 One-way ANOVA in pwr: (35:11)
4. Conclusions: (37:54)

3. Part 2 [Tutorial]

Factorial designs:

Sections:

1. Presentation: (0:00)
2. Intro to factorial designs in Superpower: (1:17)
3. Installation and loading Superpower: (6:25)
4. About post-hoc comparisons: (7:29)
5. Independent-measures design: (11:09)
6. Repeated-measures design: (25:30)
7. Mixed-measures design: (37:26)
8. How Superpower works: (46:54)
9. Conclusions: (50:21)