1. Statistics for the Social Sciences Psychology 340 Fall 2006 Repeated Measures & Mixed Factorial ANOVA

2. Statistics for the Social Sciences Outline Basics of repeated measures factorial ANOVA –Using SPSS Basics of mixed factorial ANOVA –Using SPSS Similar to the between groups factorial ANOVA –Main effects and interactions –Multiple sources for the error terms (different denominators for each main effect)

3. Statistics for the Social Sciences Example Suppose that you are interested in how sleep deprivation impacts performance. You test 5 people on two tasks (motor and math) over the course of time without sleep (24 hrs, 36 hrs, and 48 hrs). Dependent variable is number of errors in the tasks. –Both factors are manipulated as within subject variables –Need to conduct a within groups factorial ANOVA

4. Statistics for the Social Sciences Example Factor B: Hours awake 24 B 1 36 B 2 48 B 3 Factor A: Task A 1 Motor 0104001040 0315103151 6559565595 A 2 Math 1103111031 1212312123 4664446644

5. Statistics for the Social Sciences Example SourceSSdfMSF A Error (A) 1.20 13.13 1414 1.20 3.28 0.37 B Error (B) AB Error (AB) 104.60 6.10 2.60 8.10 28282828 52.30 0.76 1.30 1.01 69.00 1.29

6. Statistics for the Social Sciences Example It has been suggested that pupil size increases during emotional arousal. A researcher presents people with different types of stimuli (designed to elicit different emotions). The researcher examines whether similar effects are demonstrated by men and women. –Type of stimuli was manipulated within subjects –Sex is a between subjects variable –Need to conduct a mixed factorial ANOVA

7. Statistics for the Social Sciences Example Factor B: Stimulus Neutral B 1 Pleasant B 2 Aversive B 3 FactorA: Sex A 1 Men 4323343233 8653886538 3326133261 A 2 Women 3241332413 6467564675 2163221632

8. Statistics for the Social Sciences Example SourceSSdfMSF Between A Error (A) 0.83 20.00 1818 0.83 2.50 0.33 Within B AB Error (B) 58.10 0.07 39.20 2 16 29.00 0.03 2.45 11.85 0.01