1. Lecture 16 Psyc 300A

2. What a Factorial Design Tells You Main effect: The effect of an IV on the DV, ignoring all other factors in the study. (Compare means of different levels of IV, while ignoring [collapsing across] other IVs [ i.e., compare marginal means]) Interaction effect: When the effect of one IV on a DV differs depending on the level of a second IV. Interpret the interaction first

3. Group Activity: Main Effects and Interactions Make graphs of the following situations: Study 1  Study 2  Study 3  Study 4  Var AVar BAxB interaction p <.05 n.s. p <.05 n.s.p <.05 n.s. p <.05

4. Factorial Designs: Naming Conventions The first number is the number of levels in first IV, second number is number of levels in second IV, etc. 2 x 2 2 x 3 2 x 2 x 3 Between-subjects, repeated measures (within), mixed

5. A 2 x 3 Interaction

6. Analysis of Variance (ANOVA) Test statistic for ANOVA is F Is related to t-test ANOVA is for multiple levels of IV and multiple IVs MS between F = MS within It compares the amount of variability between groups to amount within groups

7. Interpreting the F statistic (ANOVA) Hand calculations –Calculate F (this is F obtained ). –Compare value with F in table (Table B.3. This is F critical ). To do this need to know alpha and df. –If F obtained > F critical, a significant effect. In SPSS –Look at source (summary) table –Effects with significance values less than.05 are significant.

8. ANOVA (one way) Example Do preschoolers benefit from extra practice in language skills? Groups: 1=5hrs; 2=10 hrs; 3=20 hrs 187287389 186285391 176299396 156285387 178279389 198281390 177282389 166278396 175285396 167291393

9. ANOVA Source (or Summary) Table _______________________________________ Source df SS MS F. Between groups 2 1133.07 566.54 8.80 Within groups 27 1738.40 64.39 Total 29 2871.47 _______________________________________

10. Oneway ANOVA: SPSS Output

11. Post hoc comparisons When there are more than two conditions, a significant F-test tells you that at least two means are different, but not which ones To discover which are different, we use post hoc comparisons Some of these include Scheffe, Newman-Keuls, Duncan, Tukey tests

12. SPSS: Factorial ANOVA, All Between- Subjects IVs (Weight loss data) Female trainer Female trainer Male trainer Male trainer Female client Male client Female client Male client 76658865 78907667 76657667 76907687 76655678 74907656 74907654 76799856 76708854 55907856

13. SPSS Data File: Weight Loss Study

14. SPSS Weight Loss Study Plot

15. SPSS Output File: Weight Loss Study