Learning Objectives By the end of this lesson, you will be able to: Describe factorial designs with reference to multiple levels and multiple independent variables Interpret the results of a factorial design using main effects, interactions, and simple main effects State three considerations for factorial designs Manipulating the Independent Variable Multiple Levels Level: the quantity, magnitude, or category of the independent variable being studied. These are often expressed as different conditions. There may be two or more levels of an independent variable in a study. Multiple Independent Variables Independent Variable: the variable in an experiment that is specifically manipulated or is observed to occur before the dependent variable, in order to assess its effect or influence. There may be two or more independent variables in a study. Factorial Designs Factorial Design Factorial Design: an experimental study in which two or more independent variables are simultaneously manipulated or observed in order to study their joint influence flinteraction effect) and separate influences flmain effects) on the dependent variable. Factorial Design Factorial Design: an experimental study in which two or more independent variables are simultaneously manipulated or observed in order to study their joint influence flinteraction effect) and separate influences flmain effects) on the dependent variable. Main Effect Main Effect: the consistent total effect of a single independent variable on a dependent variable over all other independent variables in an experimental design. Marginal Mean: in a factorial design, the average score of all participants in one condition of one independent variable, collapsing across all other variables. Main Effect Main Effect: the consistent total effect of a single independent variable on a dependent variable over all other independent variables in an experimental design. Marginal Mean: in a factorial design, the average score of all participants in one condition of one independent variable, collapsing across all other variables.
Interaction Effect Interaction Effect: in a factorial design, the joint effect of two or more independent variables on a dependent variable above and beyond the sum of their individual effects. The independent variables combine to have a different fland multiplicative) effect, such that the value of one is contingent upon the value of another. This indicates that the relationship between the independent variables changes as their values change. Moderating Variables Moderator: an independent variable that changes the nature of the relationship between other variables. Interactions are the identification of moderating relationships between variables. In this case, z is a second independent variable, which is dictating the relationship between x and y. Simple Main Effect Simple Main Effect: in a factorial design, the effect of one independent variable on the dependent variable, at one particular level of another independent variable. Summary: Analyzing Factorial Designs Main Effect: Blue Interaction: Purple Simple Main Effect: Red Practice 1 Main effect of A: No Main effect of B: No Interaction between A x B: No Practice 2 Main effect of A: Yes Main effect of B: No Interaction between A x B: No Practice 3 Main effect of A: No Main effect