Upon completion of this lesson, you should be able to:
- Recognize a cross-over repeated measures design.
- Understand what a wash-out period is.
- Test for the significance of carry-over effects.
- Adjust treatment means to account for carry-over effects.
In this lesson, we will be discussing the basics of cross-over designs briefly. A crossover design is a repeated measures design in which each experimental unit is given each of the different treatment levels during different time periods. This means that over time each experimental unit is assigned to a specific ordered sequence of different treatment levels. This is in contrast to a repeated-measures design in time, discussed in the previous chapter, where multiple (repeat) measurements are taken through time from the same experimental unit assigned to a specific treatment level.
- 12.1: Introduction to Cross-Over Designs
- Introduction to cross-over designs and carry-over effects.
- 12.2: Coding for Carry-Over Covariates
- Working through a sample dataset to account for carry-over effects.
- 12.3: Programming for Steer Example
- Programming for a repeated measures ANCOVA with the steer feed dataset.
- 12.4: Testing the Significance of the Carry-Over Effect
- The process to test the significance of the the carry-over effect.
- 12.5: Try It!
- Practice in cross-over repeated measure design statistical analysis.