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Lecture 16 Psyc 300A

Lecture 16 Psyc 300A. 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])

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Lecture 16 Psyc 300A

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  1. Lecture 16Psyc 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 

  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 MSbetween F = MSwithin • It compares the amount of variability between groups to amount within groups

  7. Interpreting the F statistic (ANOVA) • Hand calculations • Calculate F (this is Fobtained). • Compare value with F in table (Table B.3. This is Fcritical). To do this need to know alpha and df. • If Fobtained > Fcritical, 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 1 87 2 87 3 89 1 86 2 85 3 91 1 76 2 99 3 96 1 56 2 85 3 87 1 78 2 79 3 89 1 98 2 81 3 90 1 77 2 82 3 89 1 66 2 78 3 96 1 75 2 85 3 96 1 67 2 91 3 93

  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 76 65 88 65 78 90 76 67 76 65 76 67 76 90 76 87 76 65 56 78 74 90 76 56 74 90 76 54 76 79 98 56 76 70 88 54 55 90 78 56

  13. SPSS Data File: Weight Loss Study

  14. SPSS Weight Loss Study Plot

  15. SPSS Output File: Weight Loss Study

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