METHODS IN BEHAVIORAL RESEARCH NINTH EDITION PAUL C. COZBY Copyright © 2007 The McGraw-Hill Companies, Inc.
COMPLEX EXPERIMENTAL DESIGNS CHAPTER 10 COMPLEX EXPERIMENTAL DESIGNS
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
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
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
LINEAR VERSUS POSITIVE MONOTONIC FUNCTIONS © 2007 The McGraw-Hill Companies, Inc.
LINEAR VERSUS POSITIVE MONOTONIC FUNCTIONS © 2007 The McGraw-Hill Companies, Inc.
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
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)
INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS © The McGraw-Hill Companies, Inc.
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
INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS
INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS © 2007 The McGraw-Hill Companies, Inc.
INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS © 2007 The McGraw-Hill Companies, Inc.
INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS © 2007 The McGraw-Hill Companies, Inc.
INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS © 2007 The McGraw-Hill Companies, Inc
INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS © 2007 The McGraw-Hill Companies, Inc.
INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS © 2007 The McGraw-Hill Companies, Inc.
INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS
INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS © 2007 The McGraw-Hill Companies, Inc.
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
INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS © 2007 The McGraw-Hill Companies, Inc.
INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS © 2007 The McGraw-Hill Companies, Inc.
INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS © 2007 The McGraw-Hill Companies, Inc.
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