Repeated Measures ANOVA

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Conceptual description of Repeated Measures ANOVA - no equations for computation

Conceptual description of Repeated Measures ANOVA - no equations for computation

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  • 1.  Repeated Measures ANOVA  Types of Repeated Measures: Dependent (Paired) t -Test Within Subjects ANOVA
  • 2. Types of ANOVA
  • 3. Figure 13-3 (p. 346) The structure and sequence of calculations for ONEWAY analysis of variance. Review of Oneway ANOVA
  • 4. Figure 13-9 (p. 346) Review Equations for ANOVA.
  • 5. Remember types of t -Tests
    • Independent Samples
    • Compare two groups that are unrelated to each other
    • Numerator is difference between groups
    • Does not control for the impact of individual differences
    • Related Samples
    • Compare two measures from one person or one related pair of people
    • Numerator is difference within pair
    • Controls for the impact of individual differences
  • 6. Repeated Measures ANOVA
  • 7. Repeated Measures ANOVA (Within Subjects ANOVA)
    • Similar in concept to Paired t -Test
    • Measurement is taken on same subject or group of subjects (e.g., a family)
    • More than 2 measures are taken
    • Examples:
      • Score on Exam 1, Exam 2, Exam 3, Exam 4
      • Before meds, 4 weeks after, 8 weeks after
      • Compare mother, father, child 1, child 2
  • 8. Compare types of ANOVA
    • Oneway ANOVA
    • Means of 3 or more independent groups
    • Differences between groups measures the impact of treatment
    • Does not control for individual differences
    • Rpt Meas ANOVA
    • Three or more related measures on same people
    • Differences within each individual show the impact of treatment
    • Design controls for individual differences
  • 9. Example : Weight Watchers
    • Twenty people start Weight Watchers
      • They have tremendously different weights
    • They are weighed each week for 4 weeks
      • Each person has 3 “change” weights
        • Week 2 – Week 1
        • Week 3 – Week 2
        • Week 4 – Week 3
      • This is variability WITHIN each SUBJECT
    • If Within Subject variability is large, this shows that Weight Watchers is helping
    • Variability Between Subjects is not relevant.
  • 10. Figure 14-2 (p. 375) The partitioning of variability for a repeated-measures experiment.
  • 11. Assumptions of Repeated Measures ANOVA
    • Dependent variable is interval or ratio
    • Dependent variable is normally distributed
    • Multiple measurements for dependent variable should be from the same subjects, or paired / related subjects
  • 12. Repeated Measures ANOVA example: Blockbuster Video decides to eliminate late fees. In each Blockbuster store, they measure what percentage of videos come back late in the month before the change, the month of the change, and the month after the change. Dependent variable : Percent of Videos Late Repeated Measure : Month (before, during, or after change)
  • 13. Computations
    • Concept is similar to One-way ANOVA
      • Sums of squares computed
    • Variation WITHIN subjects is now of interest – due to treatment
      • Individual differences must be removed from the within subjects treatment
    • Variation Between Subjects is now “error” – due to random variation
  • 14. Figure 14-2 (p. 375) The partitioning of variability for a repeated-measures experiment.
  • 15.