Repeated Measures ANOVA - calculate required sample size with G*Power

// Repeated Measures ANOVA - calculate required sample size with G*Power //
The repeated measures one-way ANOVA (analysis of variance) is a parametric statistical method that is used to test the means of at least three measurements for the same test subjetcs for differences.
In the run-up to an empirical study or data collection for the repeated measures ANOVA, the necessary sample size must be determined, for example using G*Power. The minimum sample size depends on the assumed effect size (f or Eta²), the alpha level, the statistical power and the number of groups.
At the end, I show examples of different minumum sample size for the repeated measures ANOVA with different characteristics of the input parameters mentioned using G*Power
Download link:
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www.psychologie.hhu.de/arbeit...
Introduction to G*Power:
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🎥 • G*Power: A (short) Beg...
⏰ Timestamps:
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0:00 Introduction
0:08 Selecting the repeated measures ANOVA
0:17 Select type of power analysis
0:25 Input parameter I: Effect size f
1:00 Input parameter II: Alpha error probability
1:17 Input parameter III: power (1-beta error)
1:45 Input parameter IV: number of groups
1:53 Input parameter V: number of measurements
2:05 Input parameter VI: correlation among repeated measurements
2:13 Input parameter VII: Nonsphericity correction
2:24 Calculation and overview
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[@chirstinajohnson4342]

Hi,
Thank you for providing the tutorial. I have a couple of questions. I want to calculate the number of participants required for the following study.
The study is longitudinal in nature and has two groups. Data is collected at two time points. The experiment has three conditions and a control condition. I am planning to compare the two groups across time and the different experimental conditions within each group and across time. How do I calculate the number of participants required in a group for a large effect size?
Also, while selecting, should I select between factors, within or interaction?
Thank you

[@statorials]

Hi there, I would recommend doing a mixed ANOVA approach that covers between and within effects: ruclips.net/video/5AflJkhaln0/видео.html
The estimated marginal means (posthoc-testing) you mentioned, cannot be directly considered in the sample size calculation though, which is not a deal breaker.
Cheers, Björn.

[@stephanfrederic7535]

Great video! This is the case when we measure the same thing under the same condition 3 times, right? But what do I select if I have a traditional 2x2 within ANOVA design with the factors indicating different conditions, let's say measuring RTs with 2 devices (computer, paper) and cognitive load (single-task, dual-task).
Do I select just 1 group and 4 measurements in time?

[@statorials]

Hi Stephan, thanks! That sounds like you only have one variable with two conditions and also two outcomes. In that case a MANOVA would be appropriate from my point of view.
Best Regards, Björn.

[@robre9886]

@@statorials There are two independent within subject variables with two levels (Device: Computer/Paper and Task: Single-task, Dual task) so a 2w*2w design and the dependent variable is RT. So there are four conditions (Computer x Single-Task, Computer x Dual-Task, Paper x Single-Task and Paper x Dual-Task), which gives 4 measures. If we are interested in the main effects and potential interaction between the two indepdendent variables, what should be entered in G*Power to get a-priori sample size in this case?