Chapter 11: Factorial Designs

Question 1

What is a main effect?

Answer 1

difference in mean values of the levels of one factor

Question 2

What is an interaction in a factorial design?

Answer 2

when the effects of one factor depend on the level of a second factor

Question 3

What are the pros and cons of Pure between-subjects factor design?

Answer 3

Disadvantages
- many participants because all factors are between-subjects
- individual differences can be a confounding variables

Advantages
- No order effects
- Good when many participants available, individual differences are small and order effects expected

Question 4

What are the pros and cons of within-subjects factor design?

Answer 4

Disadvantages
- Carryover effects
- Time consuming
- Attrition risk

Advantages
- Fewer participants needed
- reduces individual differences

Question 5

What is a combined strategy factorial design?

Answer 5

One experimental independent variable and one quasi independent variable
- second factor is pre-existing participant characteristics (age, gender…)
- can be called person-by-environment (PxE)
- second factor can also be time

Question 6

Advantages of Factorial designs?

Answer 6

Highly efficient designs
- effect of many factors simultaneously and interactions
- can replicate and expand all in one study
Instead of reducing individual differences by holding constant (e.g., age), can include as another factor in the study
High external validity

Question 7

Disadvantages of Factorial designs?

Answer 7

More chance of having confounds than single IV designs
Interpretations are no better than correlational studies if factors are not manipulated
Too many factors make interpretation confusing
May require a more stringent alpha level due to multiple statistical tests

Question 8

What are some alternative uses of factorial designs?

Answer 8

Replication→ repeating a previous study and incorporating a new “replication” factor
- can add another factor
- extension of main findings to additional factor

Expanding the design→ add a factor in the form of new participant characteristics to reduce variance
- ex: add bilingualism and explain further the previous results
- use participant variable as another factor to reduce variance
—>reduces individual differences within each group

Using order of treatment as additional factor for within-subjects
- can test order effects existing in data
- can find no effect, symmetrical order effects or asymmetrical order effects