Chapter 10: Between-Subjects Factorial Design

Factorial Design

• contains more than one independent variable.

• can provide information about both treatment and interaction effects.

• more efficient since it combines several one-factor experiments and allows us to study interactions.

Factor

is an independent variable.

Two factor experiment

• is the simplest factorial design.

• The effect of psychotherapy (IV1) and antidepressant drugs (IV2) on depression (DV).

Main effects

• is the action of a single IV on the DV.

• There can be as many ____ as independent variables.

Interaction

• is the joint effect of two or more IVs on the DV.

• the effect of one IV is different across levels of the other IV.

Higher-order interaction

• is an interaction among three or more IVs.

• Interpretation can be difficult when more than three IVs interact in an experiment.

• Assign letters (A, B, C) to the independent variables.

• Identify all unique two- and three- treatment combinations.

• For three independent variables, these include AB, AC, BC, and ABC.

Shorthand notation

tells the number of factors involved (numerical value of each number and tell how many levels each factor has.

Factor-labeling method

• lists the two factors in parentheses after the numerical notation

• This method lists the two factors and their respective levels after the numerical notation.

• 2×2 (Type of Name x Length of Name)

External validity

A factorial design can achieve greater _____ since it can better recreate the complexity of the multivariate environment.

Number of subjects, time. interpretability of results

Practical limitations of choosing a between subject design include: