Chapter 8—Factorial Designs

Question 1

What is a factorial design?

Answer 1

When a study includes more than a single IV

Question 2

How do we read factorial designs’ numbering system?

Answer 2

x # x

#(#) = number of Independant variables

2 x 2 x 3
IV1 IV2 IV3
2 lvl 2 lvl 3 lvl

Question 3

What is a factorial matrix?

Answer 3

A row and column arrangement that characterizes a factorial design and shows the independent variables, the levels of each independent variable, and the total number of conditions (cells) in the study

Question 4

Differ between main effects and interactions

Answer 4

Main effects: whether a significant diference exists among the levels of an IV
—> Occurs when one level is significantly different than the others within an IV

Interactions: the advantage of factorials over single-factor designs. Interactions sometimes render main effects irrelevant
—> Occurs when the effect of one IV depends on the level of another IV

Question 5

What is a mixed factorial design? What is the issue with creating mixed factorial designs, and how do we solve it?

Answer 5

A design where a mixture of between-subjects and within-subjects variables exist in the same experiment

Issue: creating equivalent groups is difficult because this design is subject to the flaws of both between (unequal groups) and within subject designs (order effects).

Solution: we can use counterbalancing and RA; but we don’t always use counterbalancing when the order effects themselves are the outcome of interest

Question 6

What is a P x E factorial design? How are participants grouped?

Answer 6

A between-subjects design that includes both a subject variable and a manipulated IV; explore the interaction between the type of person in the study and the environment/situation the study produces.

Participants are grouped by their subject characteristics

Question 7

What is an ATI design?

Answer 7

A type of P x E design; aims to match aptitudes to optimal treatments. Helps improve outcomes by customizing interventions.

Question 9

What is a mixed P x E factorial design? What does it aim to do?

Answer 9

A design where the P factor is between-subjects and the E factor is within-subjects. Every participant experiences all levels of the E variable, but they belong to only one P group.

Aims to see if people respond differently to various environmental conditions depending on their personality traits

Question 10

How do ANOVAs work in factorial designs?

Answer 10

There’s an F score for each possible main effect and for each possible interaction.