1. METHODS IN BEHAVIORAL RESEARCH
NINTH EDITION
PAUL C. COZBY
Copyright © 2007 The McGraw-Hill Companies, Inc.

2. COMPLEX EXPERIMENTAL DESIGNS
CHAPTER 10
COMPLEX EXPERIMENTAL DESIGNS

3. LEARNING OBJECTIVES
Define a factorial design and discuss reasons a researcher would use this design
Describe the information provided by main effects and interaction effects n a factorial design

4. LEARNING OBJECTIVES Describe an IV x PV design
Discuss the role of simple main effects in interpreting interactions
Compare the assignment of participants in an independent groups design, a repeated measures design, and a mixed factorial design

5. 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

6. LINEAR VERSUS POSITIVE MONOTONIC FUNCTIONS
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7. LINEAR VERSUS POSITIVE MONOTONIC FUNCTIONS
© 2007 The McGraw-Hill Companies, Inc.

8. 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

9. 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)

10. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS
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11. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS
Interactions and Moderator Variables
Outcomes of a 2 x 2 Factorial Design
There may or may not be a significant main effect for independent variable A
There may or may not be a significant main effect for independent variable B
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 type of questioner
Simple main effect of type of question

12. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS

13. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS
© 2007 The McGraw-Hill Companies, Inc.

14. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS
© 2007 The McGraw-Hill Companies, Inc.

15. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS
© 2007 The McGraw-Hill Companies, Inc.

16. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS
© 2007 The McGraw-Hill Companies, Inc

17. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS
© 2007 The McGraw-Hill Companies, Inc.

18. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS
© 2007 The McGraw-Hill Companies, Inc.

19. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS

20. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS
© 2007 The McGraw-Hill Companies, Inc.

21. 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

22. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS
© 2007 The McGraw-Hill Companies, Inc.

23. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS
© 2007 The McGraw-Hill Companies, Inc.

24. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS
© 2007 The McGraw-Hill Companies, Inc.

25. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS
Increasing the Number of Levels of an Independent Variable
Increasing the Number of Independent Variables in a Factorial Design
Repeated measures
Mixed factorial design using combined assignment