Lecture 20: Factorial Designs ll

Question 1

types of factorial designs

Answer 1

• Pure (between-subjects) factors
• Within-subjects factors
• Mixed design (between + within-subjects factors)
• Higher order factorial designs: factorial designs with 3 or more factors

Question 2

pure factorial design

Answer 2

• Design in which all factors are being manipulated
• Between-groups designs: different groups of participants are randomly assigned to each cell of the design

Question 3

advantage of pure factorial designs

Answer 3

Avoids problems with order effects

Question 4

disadvantages of pure factorial designs

Answer 4

• Can require many participants because all factors are between-subjects
• Individual differences can become confounding variables (as in single-factor between-subjects designs)

Question 5

when are pure factorial designs best?

Answer 5

when many participants are available, individual differences are relatively small, and order effects might be a problem

Question 6

within-subjects factorial designs

Answer 6

A single group of participants is in all separate conditions

Question 7

advantages of a within-subjects factorial design

Answer 7

• Fewer participants are needed
• Reduces individual differences

Question 8

disadvantages of a within-subjects factorial design

Answer 8

• Many factors means that participants experience many different conditions
• Very time-consuming and the likelihood of attrition is higher
• Increases chances of testing effects (practice/fatigue)
• Makes it difficult to counterbalance orders to control order effects

Question 9

when are within-subjects factorial designs best?

Answer 9

individual differences are large and order effects will not be a problem

Question 10

mixed designs

Answer 10

a factorial study that combines both within- and between-subject factors

Question 11

when are mixed designs used?

Answer 11

• when one factor is expected to threaten validity
• when the experimenter wants the advantage of a between-subjects design for one factor, while a within-subjects design is preferable for the second factor

Question 12

common breakdown of mixed factorial designs

Answer 12

one between-subjects factor and one within-subjects factor

Question 13

Pretest-posttest control group designs

Answer 13

example of a two-factor mixed design, where one factor is a between-subjects factor and pretest-posttest is a within-subjects factor

Question 14

Higher-order factorial designs

Answer 14

more complex designs involving 3 or more factors
In the three-factor design, the researcher evaluates the main effects for each of the three factors, plus three two-way interactions, and one three-way interaction

Question 15

should you use more than 3 factors?

Answer 15

you should try to avoid more than 3 factors in factorial designs unless you have clear predictions for interactions

Question 16

advantages of factorial designs

Answer 16

• Highly efficient designs that allow studying the effect of many factors simultaneously, interactions of factors, and replicate and expand upon existing study all in one study
• Instead of reducing individual differences by holding constant (ex. age), can include as another factor in the study
• Complex nature provides real advantages, but also some challenges (especially interpretation)
• High external validity

Question 17

disadvantages of factorial designs

Answer 17

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

Question 18

statistical analysis of factorial designs depends on whether the factors are:

Answer 18

• Between-subjects
• Within-subjects
• Some mixture of between- and within-subjects

Question 19

standard procedure for statistical analysis of factorial designs

Answer 19

• Computing the mean for each treatment condition (cell)
• Using ANOVA to evaluate the statistical significance of the mean differences

Question 20

other uses of factorial designs

Answer 20

1. replication
2. expanding the design
3. using the order of treatments as an additional factor

Question 21

replication

Answer 21

repeating a previous study and incorporating a new replication factor (first/second replication)

Question 22

expanding the design

Answer 22

adding factors in the form of new participant characteristics

Question 23

purpose of expanding the design

Answer 23

to reduce the variance within groups by using the specific variable as a second factor

Question 24

benefits of expanding the design

Answer 24

• Greatly reduces individual differences within each group
• Does not sacrifice external validity

Question 25

using the order of treatments as an additional factor

Answer 25

makes it possible to evaluate any order effects that exist in the data

Question 26

3 possible outcomes of using the order of treatments as an additional factor

Answer 26

• No order effects
• Symmetrical order effects: same order effects across other factors
• Asymmetrical order effects: order interacts with other factors

Question 27

why does using the order of treatment as an additional factor help reduce variance?

Answer 27

• The randomization of participants to conditions does not always remove bias from unknown extraneous variables
• It is not possible to always randomize condition orders when there are many conditions