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Chapter 10: Complex Experimental Designs

Psychology 201

Franchesca Basilan

on 16 October 2012

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Transcript of Chapter 10: Complex Experimental Designs

Chapter 10: Complex Experimental Designs Increasing the Number of Levels of An Independent Variable Analysis of variance Interactions and Simple Main Effects To increase the complexity of an experiment, increase the levels of an independent variable Increasing the Number of Levels of an Independent Variable 2 basic ways of assigning participants to conditions Assignment Procedures and Factorial Designs A 2 x 2 x 2 factorial design has 3 variables with 2 levels; (which means 8 conditions in a design etc) But the rule for constructing factorial designs remain the same throughout Increasing the Number of Independent Variable in a Factorial Design Increasing the Number of Independent Variables: Factorial Designs It is possible to design an experiment with more than one variable. Factorial Designs Simplest factorial design = 2 x 2 Number of
Levels of first IV x Number of levels of second IV Number of levels of third IV x Interpreting Factorial Designs Main effect = the effect each variable has by itself

Interaction = interaction between 2 independent variables.
- The effect of one independent variable depends on the certain level of the other variable. Factorial Designs with Manipulated & Non-Manipulated Variables a.k.a. IV x PV Designs This shows how different types of participants will respond to the same manipulated variables Interactions and Moderator Variables Moderator variables = it influences the relationship between 2 other variables; which can
be certain situations or the characteristics of people. Outcomes of 2 x 2 Factorial Designs Simple Main Effects independent group design

repeated measure design Mixed Factorial Design The problem with a study with to many independent variables is that it becomes too complex and need large number of participants Lizette and Franchesca This presentation was brought to you by... 1)May or may not be a significant main effect for independent variable A 2)May or may not be a significant main effect for independent variable B 3)May or may not be a significant interaction for independent variables
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