Mixed ANOVA in SPSS - calculation and interpretation in 6 minutes

This video shows how to conduct the mixed ANOVA in SPSS and interpret the output.
➡️ Watch next: • Mixed ANOVA in SPSS - ...
General information:
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The mixed ANOVA is a parametric statistical method that is used when you have a test variable for multiple points in time for the same individiuals AND multiple groups. This test is used to assess whether the means over time (within-subjects effect), between groups (between-subjects effect) or a combination of both (interaction effect) show a difference.
Follow this SPSS tutorial for the mixed ANVOA to conduct it step by step and interpret the output.
📌 Hint: If you can observe a interaction effect, do NOT interpret the main effects. You just found out that the two effect depend on each other, i.e. they should not be interpreted seperately while holding the other effect constant respectively!
Requirements:
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- The dependent variable needs to be on the interval or ratio scale. Furthermore, the dependent variable should be approximately normally distributed for each point in time per group ( • Mixed ANOVA in SPSS - ... ).
- Homogeneity of variance for the between-subject factor at each level of the within-subject factor ( • Homogeneity of Varianc... )
- Homogeneity of covariances of the between-subject factor ( • Checking Homogeneity o... )
- Equal variances of the differences for the measurements, also called sphericity - (for 3 or more measurements over time)
The requirement of sphericity will also be tested within this video since it is based on the model calculation. Sphericity describes the homogeneity of the variances of the pairwise differences over time. In case you have no sphericity, the Greenhouse-Geisser and Huynh-Feldt corrections can be applied. The choice is also discussed within this video, with the help of Field (2018), Discovering Statistics, p. 556-658. The interpretation with a correction does not differ from without a correction.
For example:
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I want to test a new drug for efficacy. I will divide my sample into two groups - an intervention group and a control group. This controls for the between-subject effect. Furthermore, I want to see the results over time, there I'll establish a baseline measurement and four follow-up measurements. This will take care of the within-subject effect.
Calculating the required sample size:
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🎥 • Mixed ANOVA - calculat...
I split up the pos-hoc analysis into a significant (🎥 UPCOMING) and non-significant interaction (🎥 UPCOMING) using estimated marginal means.
⏰ Timestamps:
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0:00 Introduction and example
0:24 Requirements for the mixed ANOVA
1:20 Define mixed ANOVA model in SPSS
2:49 Descriptive statistics as a first look
3:04 Sphericity testing
4:24 Interpreting the interaction effect
5:08 Interpreting the main effects
If you have any questions or suggestions regarding mixed ANOVA in R - calculation and interpretation, please use the comment function. Thumbs up or down to decide if you found the video helpful. #statisticampc #statorials
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[@weizhang8133]

Very useful😀

[@statorials]

Glad you like it!