Two-Way Repeated Measures ANOVA

TABLE OF CONTENTS:

18–A: 'Tidying' Your Data

We will be introducing tidyverse packages in R during this lesson. The tidyverse (https://www.tidyverse.org/) is a collection of packages in R for data science. These packages all share a common design philosophy, grammar, and data structure so they can work in harmony together.

Specifically, we will introduce data transformations using the spread and gather packages. to tidy our data – in other words, to get them into the format used by the tidyverse. The following images from Allison Horst detail why and how it is important to tidy our data as well as visually depict how spread and gather alter our data. We also cover this in detail in our video.

18–B: Introduction and Learning Outcomes (1:28)

18–C: Loading Packages and our Dataset (8:43)

18–D: Research Question and Hypotheses (4:44)

18–E: Preparing our Data: Creating an ID Variable (5:05)

18–E: Preparing our Data: Converting Data from Wide Format to Long Format (9:20)

18–F: Testing Assumptions (8:44)

18–G: Analyses and Interpretation (7:28)

18–H: Effect Sizes (3:15)

18–I: If You Have a Significant Interaction (10:02)

18–J: If You Do Not Have a Significant Interaction (3:45)

18–K: Post-Hoc Analyses (2:55)

18–L: Pairwise Comparisons for Conditional Effects (12:35)

18–M: Pairwise Comparisons for Main Effects (5:20)

18–M: Final Write-Up (15:59)

18–N: Depicting the Results (6:10)