Factorial Designs Unit 9

Question 1

What is a factorial design?

Answer 1

Where two or more independent variables are manipulated simultaneously to determine their separate or combined effects on the dependent variable

Question 2

2 types of effects

Answer 2

1. Main effect - influence of one factor on the dependent variable (there is a main effect for a mean when there is a significant difference between both mean numbers - LINES ARE PARALLEL)
2. Interaction effect - the influence of one factor on the other factor (in a graph - its an interaction ONLY if the two lines cross or look as if they will cross)

**when both effects are significant, then only the interaction effect is considered

Ex) Whenever it is necessary to say something like the following, you are looking at an interaction: The effect of smiling on judged guiltiness depends on the attractiveness of the faces; specifically, smiling reduces the judged guiltiness of unattractive faces, but increases the judged guiltiness of attractive faces.

Question 3

What are the advantages of using factorial designs?

Answer 3

Produce greater precision than single-factor designs

A potentially confounding variable can be built into the design by including that confounding variable as a factor in factorial design

Question 4

2X2 factorial design

Answer 4

Two variables, each of which has two values, or levels. This is known as a two-by-two (2 × 2) factorial design because of the two levels of each variable

Question 5

3 types of interaction effects

Answer 5

1. antagonistic interaction - interaction in which the two independent variables tend to reverse each other’s effects
2. synergistic - interaction in which the two independent variables reinforce each other’s effects
3. ceiling effect - interaction in which one variable has a smaller effect when paired with higher levels of a second variable

Question 6

What is best choice when considering between-subjects, within-subjects and mixed subjects?

Answer 6

The within-subjects design requires only eight subjects to obtain eight responses in each of the four conditions. The mixed design requires 16 subjects to obtain the same number of responses. The between- subjects design is the least efficient, requiring 32 subjects. Whenever it is possible to present each condition to every subject, the within-subjects design should be considered,