1. Complex Experimental Designs

2. INCREASING THE NUMBER OF LEVELS OF AN INDEPENDENT VARIABLE Provides more information about the relationship than a two level design Curvilinear Relationship Inverted-U Comparing Two or More Groups I.E. How dogs, cats, and birds as opposed to dogs alone have beneficial effects on nursing home residents

3. LINEAR VERSUS POSITIVE MONOTONIC FUNCTIONS

5. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS Factorial Designs: Designs with more than one independent variable (or factor) Simplest Factorial Design 2 x 2 factorial design Has two independent variables

6. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS Interpretation of Factorial Designs Main effects of an independent variable Interaction between the independent variables Factorial Designs with Manipulated and Nonmanipulated Variables IV x PV designs (Independent Variable by Participant Variable)

7. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS Interactions and Moderator Variables Outcomes of a 2 x 2 Factorial Design 1.There may or may not be a significant main effect for independent variable A 2.There may or may not be a significant main effect for independent variable B 3.There may or may not be a significant interaction between the independent variables (See results in next five slides) Interactions and Simple Main Effects Simple main effect of anxiety Simple main effect of studying

8. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS A

14. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS Assignment Procedures and Factorial Designs Independent groups design Repeated measures design Mixed factorial design using combined assignment

15. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS

18. Increasing the Number of Levels of an Independent Variable 2 x 3 Increasing the Number of Independent Variables in a Factorial Design 2x2x3 = 12 conditions! Gets unwieldy pretty quickly

19. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS