Chapter 9 – Factorial Designs

1 / 31

# Chapter 9 – Factorial Designs - PowerPoint PPT Presentation

Chapter 9 – Factorial Designs. Factorial Design -- definition Two or more IVs every level of one IV combined with every level of other IV IVs -- called factors. Example: memory for words. Factors. word type (noun or verb) word length (short or long). Numerical notation. Denotes:

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

## PowerPoint Slideshow about ' Chapter 9 – Factorial Designs' - merritt-koch

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Chapter 9 – Factorial Designs
• Factorial Design -- definition
• Two or more IVs
• every level of one IV
• combined with every level of other IV
• IVs -- called factors
Factors
• word type (noun or verb)
• word length (short or long)
Numerical notation
• Denotes:
• Number of IVs (factors)
• Number of levels of each factor
• e.g. 2 x 2 design
• e.g., 4 x 3 design
Factorial Table
• One factor rows – Other factor columns
• Each column / row corresponds to a level of its factor
• Each cell represents a specific condition
• Combination of specific levels of each factor
• note: #conditions = levels x levels
Alternative labeling scheme
• word type = factor A
• length = factor B)
• 4 Conditions
• noun / short: A1B1
• noun / long: A1B2
• verb / short: A2B1
• verb / long: A2B2
Results of Factorials:

Word Length

Short

Long

Word

Type

Noun

7.5

5.5

6.5

Verb

6

4

5

6.75

4.75

• Main effects & Interactions
• Main Effect
• effect of one IV independent of other IV
• collapse across levels of other IV
• compute and compare marginal means
Results of Factorials
• Interaction between factors (IVs)
• Ask: does effect of on IV depend on the level of the other IV?
• If the answer is “yes” – you have an interaction
• easiest way to see interaction -- in a line graph
Results of Factorials
• Can plot either way -- same interpretation
Example 2:

Comic Book

Violent

NonViolent

Sex

Girl

3

2.5

2.75

Boy

8

4

6

6.5

3.25

• Effect of violent media on 6th grade children
• IV1: Comic book content (violent vs. nonviolent)
• IV2: Sex of subject (male vs. female)
• DV: Measure of aggressiveness (response to scenario)
Interaction
• Does type of comic book have effect? -- it depends
• Does sex matter? -- it depends
Interaction
• Can plot either way
Possible patterns
• can get any possible combination of main effects and interactions
• main effects but no interactions
• interactions but no main effects
• main effect of one factor, but not the other
• **INTERPRETATION:
• INTERACTION SUPERCEDES MAIN EFFECTS

Comic Book

Violent

NonViolent

Sex

Girl

3

3

3

Boy

8

8

8

5.5

5.5

Comic Book

Violent

NonViolent

Sex

Girl

8

3

5.5

Boy

8

3

5.5

8

3

Comic Book

Violent

NonViolent

Sex

Girl

3

3

3

Boy

3

3

3

3

3

Comic Book

Violent

NonViolent

Sex

Girl

2

4

3

Boy

8

6

7

5

5

Comic Book

Violent

NonViolent

Sex

Girl

4

8

6

Boy

8

4

6

6

6

Types of Factorials
• Between Subject Factorials
• Within Subject (Repeated Measures) Factorials
• Mixed Factorials
• IV x PV Factorials
Between Subjects Factorial
• all factors(IV) are manipulated between subjects
• e.g., study material by material generation (2x2 between subject design)
• study material – outline vs. questions
• material generation – self vs. instructor
• four conditions: four different groups of subjects
• concerns: begin with equivalent groups
• random assignment
• matching
Within Subjects Factorial
• all factors(IV) are manipulated within subject
• e.g., effect of sex and age of approacher on personal space
• (2x3 within sub design)
• 2 levels of sex (f vs. m)
• 3 levels of age (20’s, 40’s, 60’s)
• 6 different conditions (6 different people approaching
• concerns: sequence or carryover effects
• complete counterbalancing
• partial counterbalancing (Latin Square)
Mixed Factorial Designs
• at least one factor (IV) manipulated between
• at least one manipulted within
• e.g., add the factor of mood into above design
• (3x2x3 mixed factorial design)
• sex and age are manipulated within subject
• perform a between subject mood manipulation:
• Positive, Neutral, or Negative
• concerns: equivalence for between subject factors
• concerns: carryover effects for within subject factors
IV x PV designs
• At least one manipulated IV
• At least one subject variable
• e.g., Personality Type (Type A or Type B) x competition (hi or low)
• DV -- problem solving task
• Main Effect of PV -- effect of person type
• Main effect IV -- task/situation effect
• Interaction -- task/situation differences depend on person type
• ** Must be careful in interpreting subject variables (as always)
Higher order designs
• Three or more factors (IVs)
• Each level crossed with every other
• Each factor – may produce main effect
• May have interaction between any combination of factors
Higher Order Designs
• 2x3x2 Design
• Personality Type x Caffeine level x Sex
• DV: Problem solving speed
Higher Order Designs
• Main Effect of Sex
Higher Order Designs
• Main Effect of Caffeine Level
Higher Order Designs
• Main Effect of Personality Type
Interactions
• Two Way Interactions
• Personality Type x Caffeine Level
• (average across sex)
• Personality Type x Sex
• (average across caffeine level)
• Caffeine Level x Sex
• (average across personality type)
• Three Way Interaction
• Two-way interaction DEPENDS on level of other variable