Chapter 11: Factorial Designs

Flashcards for Chapter 11 on Factorial Designs.

Advantages of Factorial Designs over single-factor designs

Study multiple IVs simultaneously, detect interactions, combine one-factor ANOVAs, efficient data use.

Main Effect

Effect of one IV, averaged over all levels of the other variables.

Interaction Effect

Effect of one IV depends on the level of another IV.

Combinations of Effects

Possible to have any combination of interaction and
main effects (all effects are independent of one
another)
• In a 2 x 2 experiment, eight outcomes are possible

Significant interaction effects

Significant time of day effects no other interaction effects

Significant intensity of exercise and time of day effects no interaction effects

Graphing Combinations of Effects

Show if lines are parallel (no interaction) or cross/diverge (interaction).

Types of Interaction Effects

Synergistic, antagonistic, ceiling/floor effects.

Synergistic Interaction

Type of interaction in which two IVs tend to

increase each other’s effects

ceiling/floor effects.

Type of interaction in which one IV has a smaller effect when paired with higher levels

of a second variable

Can also be a “floor effect” if in the reverse

Antagonistic Interaction

Type of interaction when two IVs tend to

reverse each other’s effects

Types of Factorial Designs

Within-subjects, between-subjects, mixed factorial designs.

Within-subjects: definiton

 each subject experiences each condition.

Between-subjects:  definition

separate groups get each condition, requiring

more subjects to get responses to each condition.

Mixed-factorial:definition

At least one between-subjects variable and at

least one within-subjects variable

Within-Subjects Application

Controls individual differences, fewer subjects.

Between-Subjects Application

Avoids order effects, needs more subjects.

Mixed Designs Application

Combine both, control for some individual differences.

Factorial Notation

Number of factors, levels per factor, total conditions.

Calculate Conditions

Within: total conditions = measurements; Between: total conditions = groups; Mixed: depends on levels.

Subjects and Power

Within: fewest; mixed: moderate; between: most.

Within-subjects factorial design (e.g., 3×2)

6 conditions 6 measurements) Only one sample (group) is needed

Between-subjects factorial design(e.g., 4×3):

12 conditions one measurement 12 separate groups/samples

mixed-factorial designs (e.g. A x B : 4 x 2)signs (e.g. A x B : 4 x 2

(8 conditions. (4 measurements) 2 samples)