Power Analysis and Sample Size Planning - Online Course
A 3-Day Livestream Seminar Taught by
Christopher L. Aberson10:00am-2:00pm ET (New York time): Live lecture via Zoom
4:00pm-5:00pm ET: Live lab session via Zoom (Thursday and Friday only)
Statistical power analysis addresses the question “How large a sample do I need?” Alternatively, sample size may be determined by other factors (e.g., cost), and researchers then need to determine how much power the design affords for detecting effects of various sizes (sensitivity). Although many tools exist for calculating power and sample size for simple designs, these tasks can become quite daunting for more complex situations (e.g., designs with multiple predictor variables or mediation).
This seminar focuses on power for detecting effects across a wide range of research designs. It begins with a discussion of basic theoretical issues, such as why power is important and factors affecting power. The course then moves on to examine and demonstrate power and sensitivity approaches for designs that include t-tests, chi-square, multiple regression, logistic regression, ANOVA (between, within, and mixed designs), and mediation.
Starting November 18, we are offering this seminar as a 3-day synchronous*, remote workshop. Each day will consist of a 4-hour live lecture held via the free video-conferencing software Zoom. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.
Each day will include a hands-on exercise to be completed on your own after the lecture session is over. An additional lab session will be held Thursday and Friday afternoons, where you can review the exercise results with the instructor and ask any questions.
*We understand that scheduling is difficult during this unpredictable time. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.
Closed captioning is available for all live and recorded sessions.
More details about the course content
For each topic, there is a strong focus on “how-to” examples for conducting analyses using the pwr2ppl R package. Attendees will also receive code and examples for analyses using other software (e.g., Stata, G*Power, SPSS).
Participants in this seminar can expect to come away with:
- A conceptual understanding of power and the factors that affect power.
- An understanding of common misconceptions and pitfalls in conducting power analysis.
- An appreciation for design and analysis issues that impact power (e.g., multiple predictors, scale reliability).
- Experience with software for conducting statistical power and sensitivity analyses.
- Practical tools and strategies for conducting power/sensitivity analyses across a wide range of research designs.
For each topic, there is a strong focus on “how-to” examples for conducting analyses using the pwr2ppl R package. Attendees will also receive code and examples for analyses using other software (e.g., Stata, G*Power, SPSS).
Participants in this seminar can expect to come away with:
- A conceptual understanding of power and the factors that affect power.
- An understanding of common misconceptions and pitfalls in conducting power analysis.
- An appreciation for design and analysis issues that impact power (e.g., multiple predictors, scale reliability).
- Experience with software for conducting statistical power and sensitivity analyses.
- Practical tools and strategies for conducting power/sensitivity analyses across a wide range of research designs.
Computing
This seminar will use R for examples and exercises. Very little previous experience with R is needed as most analyses require a single line of code. Code in SPSS and Stata, as well as extra examples via G*Power (where applicable), will also be provided.
If you’d like to take this course but are concerned that you don’t know enough R, there are excellent on-line resources for learning the basics. Here are our recommendations.
This seminar will use R for examples and exercises. Very little previous experience with R is needed as most analyses require a single line of code. Code in SPSS and Stata, as well as extra examples via G*Power (where applicable), will also be provided.
If you’d like to take this course but are concerned that you don’t know enough R, there are excellent on-line resources for learning the basics. Here are our recommendations.
Who should register?
This course will be helpful for researchers in any field who design or conduct research studies. This should be especially useful for researchers submitting grant proposals that require power analysis. It will be helpful to have a basic understanding of power, effect size, and the analytic methods listed in the outline below.
This course will be helpful for researchers in any field who design or conduct research studies. This should be especially useful for researchers submitting grant proposals that require power analysis. It will be helpful to have a basic understanding of power, effect size, and the analytic methods listed in the outline below.
Seminar outline
Day 1
- What is power?
- Factors affecting power
- Power vs. sensitivity
- Power for chi-square and tests of proportions
- Power for t-tests
- Computational estimates of power
- Power for between subjects ANOVA
Day 2
- Power for between subjects ANOVA/additional ANOVA resources
- Power for correlation
- Power for multiple regression
- Power for moderated regression
- Power for logistic regression
Day 3
- Power for mediator and conditional processes
- Deep dive into building simulations for complex designs (e.g., multilevel models, structural equation modelling)
- Replications
- Equivalence testing (non-inferiority) loops and other useful approaches
- How to report power analyses
Day 1
- What is power?
- Factors affecting power
- Power vs. sensitivity
- Power for chi-square and tests of proportions
- Power for t-tests
- Computational estimates of power
- Power for between subjects ANOVA
Day 2
- Power for between subjects ANOVA/additional ANOVA resources
- Power for correlation
- Power for multiple regression
- Power for moderated regression
- Power for logistic regression
Day 3
- Power for mediator and conditional processes
- Deep dive into building simulations for complex designs (e.g., multilevel models, structural equation modelling)
- Replications
- Equivalence testing (non-inferiority) loops and other useful approaches
- How to report power analyses
Payment information
The fee of $895 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.
The fee of $895 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.