1. Repeated Measures ANOVA patterns over time

2. Case Study

3. One-Way Repeated Measures One-way Repeated Measures Designs are used when: One-way Repeated Measures Designs are used when: – the same subjects are measured on 3 or more occasions – the same subjects are exposed to 3 or more treatments – the same subjects provide three or more ratings that are measured on the same scale – the same subjects receive 3 or more doses of the treatment

4. Examples The same subjects are assessed on pre, mid, and post treatment occasions. The same subjects are assessed on pre, mid, and post treatment occasions. The same subjects are given three different types of medication. The same subjects are given three different types of medication. The same subjects rate three different aspects of school climate. The same subjects rate three different aspects of school climate.

5. Examples

6. Examples

7. One-Way Repeated Measures This design is analogous to the One- way ANOVA we studied earlier in the semester. This design is analogous to the One- way ANOVA we studied earlier in the semester. One-Way ANOVA designs have a single Between-Subjects IV. One-Way ANOVA designs have a single Between-Subjects IV. One-Way Repeated Measures designs have a single Within-Subjects IV. One-Way Repeated Measures designs have a single Within-Subjects IV.

8. One-Way Repeated Measures Just like the One-way ANOVA procedure is an extension of the Independent t-test, the One-Way Repeated Measures procedure is an extension of the dependent t- test. Just like the One-way ANOVA procedure is an extension of the Independent t-test, the One-Way Repeated Measures procedure is an extension of the dependent t- test.

9. One-Way Repeated Measures Data from each subject occurs in multiple cells in the design. Data from each subject occurs in multiple cells in the design. In Between-Subjects designs, data from each subject occurs in only one cell in the design. In Between-Subjects designs, data from each subject occurs in only one cell in the design.

10. One-Way Repeated Measures Just like the One-Way ANOVA procedure, a statistically significant overall F test only tells you that there is difference somewhere among the means. Just like the One-Way ANOVA procedure, a statistically significant overall F test only tells you that there is difference somewhere among the means. Post hoc comparisons are needed to detect where the difference(s) lie. Post hoc comparisons are needed to detect where the difference(s) lie.

11. Special Considerations Additional potential threats to the validity of this type of design: Additional potential threats to the validity of this type of design: – practice effects – order effects – fatigue effects – carry-over effects – ceiling and floor effects

12. Assumptions If you take the univariate approach to Repeated Measures designs, you have a new assumption: If you take the univariate approach to Repeated Measures designs, you have a new assumption: – Sphericity (replaces homogeneity of variance) – Consistent pattern to the variances and correlations

13. Assumptions If you take the multivariate approach to Repeated Measures designs, you do not have the Sphericity assumption. If you take the multivariate approach to Repeated Measures designs, you do not have the Sphericity assumption. Homogeneity of variance- covariance matrices becomes important when there are multiple groups. Homogeneity of variance- covariance matrices becomes important when there are multiple groups.

14. Assignments For Assignment 7, focus on completing an analysis and write-up for one Oneway ANOVA with Repeated Measures. For Assignment 7, focus on completing an analysis and write-up for one Oneway ANOVA with Repeated Measures.

15. Our Research Design