Factorial designs and interactions

Content

• Between vs within-subject designs
• Interactions
• Simple, marginal and interaction contrasts

Learning objectives

At the end of the session, students should be capable of

• listing the benefits of factorial designs
• interpreting an interaction plot and being aware of it’s limitation
• interpreting model effects in sum-to-zero parametrization
• reporting results from a two-way analysis of variance
• determining whether or not simple or main effects are most suitable for comparisons

Readings

• Chapter 4 of Meier (2022)
• Chapter 5 of the course notes

Complementary readings

• Chapter 7 of Maxwell et al. (2017).
• Chapters 10–13 of Keppel & Wickens (2004).

Slides

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Tip

Fun fact: If you type ? (or shift + /) while going through the slides, you can see a list of slide-specific commands.

Code

• R script
• SPSS script

References

Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher’s handbook. Pearson Prentice Hall.

Maxwell, S. E., Delaney, H. D., & Kelley, K. (2017). Designing experiments and analyzing data: A model comparison perspective (3rd ed.). routledge. https://doi.org/10.4324/9781315642956

Meier, L. (2022). ANOVA and mixed models: A short introduction using R (Chapman & Hall/CRC, Eds.). https://doi.org/10.1201/9781003146216