Chapter 9: Factorial Designs

Factorial designs

Experiments that include more than one independent variable in which each level of one independent variable is combined with each level of the others to produce all possible combinations.

Factorial design table

Shows how each level of one independent variable is combined with each level of the others to produce all possible combinations in a factorial design.

Between-subjects factorial design

All of the independent variables are manipulated between subjects.

Mixed factorial design

A design which manipulates one independent variable between subjects and another within subjects.

Non-manipulated Independent variable

An independent variable that is measured but is non-manipulated.

Main effect

The effect of one independent variable on the dependent variable—averaging across the levels of any other independent variable(s).

Interaction effect

The effect of one independent variable on the dependent variable—averaging across the levels of any other independent variable(s).

Types of interactions

Spreading interactions

cross-over interaction

Cross-over interaction

Means the independent variable has an effect at both levels but the effects are in opposite directions.

Spreading interactions

Means there is an effect of one independent variable at one level of the other independent variable and there is either a weak effect or no effect of that independent variable at the other level of the other independent variable.

Simple effects

Are a way of breaking down the interaction to figure out precisely what is going on.