2. Complex Experiments

3. Basic Experiment Simplest experimental design –Two levels of one independent variable Compares only two groups

4. Factorial Designs: Increasing the Number of Independent Variables Typically, two or three IVs are operating simultaneously (in the real world) Factorial designs include at least 2 IVs All levels of each IV are combined with all levels of the other IVs Simplest factorial is a 2 X 2 factorial design

5. A Tasty Example 2 X 2 Factorial Design Factor A (IV1): Type of Topping Level 1 = Ketchup Level 2 = Salsa Factor B (IV2): Type of Food Level 1 = French Fries Level 2 = Tortilla Chips DV: Liking of taste

6. Other Factorial Designs 3 X 4 Factorial Design 2 X 3 Factorial Design 2 X 2 X 2 Factorial Design Identify the number of experimental conditions in each of these designs.

8. Main Effects and Interactions Interpretation of Factorial Designs : –A main effect tells us the effect each variable has by itself. –An interaction tells us that the effect of one independent variable depends on the particular level of the other.

9. For each example, determine: Is there a main effect for Type of Topping? Is there a main effect for Type of Food? Is there an interaction? Describe the graph in words (is there a moderator?).

10. 1.

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20. Simple Main Effects Remember, main effects are looking at an OVERALL effect of one IV across levels of the other IV (we examine the average of both levels). We examine simple main effects when we isolate the effect of one IV at each level of the other IV.

21. Example: Berkowitz and LePage (1967) 2 X 2 Factorial Design Factor A (IV1): Presence of a Weapon Level 1 = Gun Level 2 = Badminton Racket Factor B (IV2): Amount of Provocation Level 1 = High Provocation Level 2 = Low Provocation DV: Aggression: Number of shocks delivered

22. Berkowitz and LePage (1967)

24. Brown, Novick, Lord, & Richards (1992)

26. IV x PV Designs Factorial designs with manipulated and nonmanipulated variables (sometimes called IV x PV designs –Independent variable (IV) x participant variable (PV) –Allows researchers to examine how different individuals respond to the same manipulated IV

27. Orth-Gomer et al. (2000)

28. PV x PV design Forehand and Perkins (2005) studied consumer reactions to ads with celebrity voiceovers. They found that prior attitudes toward the celebrities influenced how much consumers liked or disliked the products, but this influence was greatest when consumers weren't sure which celebrity provided the voice-over. Participants liked the product more if: –they liked the celebrity doing the voiceover AND –they did NOT recognize the celebrity’s voice in the ad

29. Between and Within Group Designs Assignment procedures and factorial designs –Two basic ways of assigning participants to conditions 1. Between (Independent) groups design 2. Within (Repeated measures) design Combination of the two basic ways is called a mixed factorial design

33. Example: Silverman et al (1978) Male’s ability at dart- throwing before and after subliminal presentation of a message “Beating Dad is OK” Poor design: Before Message After Message XXXXXXXX XXXXXXXX XX