Complex Experimental Designs

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Presentation transcript:

Complex Experimental Designs

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

Increasing the Number of Independent Variables Manipulate more than one IV Typically, two or three IV’s are operating simultaneously - Closer approximation of real-world conditions

Factorial Designs Factorial designs More than one IV (or factor) All levels of each IV are combined with all levels of the other IV’s Simplest factorial is a 2 X 2 factorial design

Berkowitz 2 X 3 Factorial Design Factor A (IV1): Mood State Level 1 = Happy Level 2 = Neutral Level 3 = Sad Factor B (IV2): Self Awareness Level Level 1 = Mirror Level 2 = No Mirror DV: Helping Behavior

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

Main Effects and Interactions Interpretation of Factorial Designs Two kinds of information Main effect of an independent variable Interaction between the independent variables

Main Effects and Interactions 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. Outcomes of a 2 X 2 factorial design Interactions and simple main effects

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

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