Complex Experimental Designs. INCREASING THE NUMBER OF LEVELS OF AN INDEPENDENT VARIABLE Provides more information about the relationship than a two level.

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Presentation transcript:

Complex Experimental Designs

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

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 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

INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS A

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

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

INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS

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