# PSYC 2040 Lecture Notes - Situation Two, Effect Size, Repeated Measures Design

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Published on 12 Apr 2013

Department

Psychology

Course

PSYC 2040

Professor

Split-Plot Analysis of Variance Part II:

Exploring the Interaction!

"

1) Interaction Overview!

2) Two types of situations with different error terms"

!

3) Situation 1: Comparing effect of the between-subjects factor at a particular level of

the within-subjects factor!

4) Situation 1: Denominator calculations!

5) Situation 1: Numerator calculations!

6) Situation 1: F-values and signiﬁcance!

7) Situation 1: Effect size calculation!

8) Situation 1: Sample Results Paragraph!

9) Situation 2: Comparing effect of the within-subjects factor at a particular level of the

between-subjects factor!

10) Situation 2: Understanding the SPSS syntax!

11) Situation 2: Understanding SPSS Output!

12) Situation 2: Effect size calculation!

1

Split-Plot Analysis of Variance Part II:

Exploring the Interaction!

"

1) Interaction Overview!

2) Two types of situations with different error terms**"

!

3) Situation 1: Comparing effect of the between-subjects factor at a particular level of

the within-subjects factor!

4) Situation 1: Denominator calculations!

5) Situation 1: Numerator calculations!

6) Situation 1: F-values and signiﬁcance!

7) Situation 1: Effect size calculation!

8) Situation 1: Sample Results Paragraph!

9) Situation 2: Comparing effect of the within-subjects factor at a particular level of the

between-subjects factor!

10) Situation 2: Understanding the SPSS syntax!

11) Situation 2: Understanding SPSS Output!

12) Situation 2: Effect size calculation!

2

Investigating a significant

2-way interaction

Split-Plot design

2-way interaction

The effect of 1 factor on the DV varies depending on the level

of the other factor

The simple main effects of 1 factor are different

at the various levels of the other

Simple Main Effect

The effect of a factor (e.g., audience) at a specific level of

another factor (e.g., males)

3

To understand an interaction, need to conduct simple main effect

analyses

1) check out the interaction cell means

2) which set of simple main effects makes more sense theoretically?

3) do the math

what we do in SPSS depends on which set of simple main effects

we want

4

0

2

4

6

8

10

Mean number of nosepicks

0 1 2 3

Audience

Gender by Audience Interaction

Women

Men

5

Problem: The Error term for SME

depends upon the situation

2 Situations

1) Examining a Between-Subject

independent variable at a

specific level of a Within-

Subjects variable

2) Examining a Within-Subjects

variable at a specific level

of a Between-Subjects

independent variable

aud0 aud1 aud2 aud3

males 8.0 6.2 4.2 4.0

females 9.8 6.4 3.0 2.0

Audience

aud0 aud1 aud2 aud3

males 8.0 6.2 4.2 4.0

females 9.8 6.4 3.0 2.0

Audience

6

Split-Plot Analysis of Variance Part II:

Exploring the Interaction!

"

1) Interaction Overview!

2) Two types of situations with different error terms"

!

3) Situation 1: Comparing effect of the between-subjects factor at a particular level of

the within-subjects factor**!

4) Situation 1: Denominator calculations!

5) Situation 1: Numerator calculations!

6) Situation 1: F-values and signiﬁcance!

7) Situation 1: Effect size calculation!

8) Situation 1: Sample Results Paragraph!

9) Situation 2: Comparing effect of the within-subjects factor at a particular level of the

between-subjects factor!

10) Situation 2: Understanding the SPSS syntax!

11) Situation 2: Understanding SPSS Output!

12) Situation 2: Effect size calculation!

7

Problem: The Error term for SME

depends upon the situation

aud0 aud1 aud2 aud3

males 8.0 6.2 4.2 4.0

females 9.8 6.4 3.0 2.0

Audience

aud0 aud1 aud2 aud3

males 8.0 6.2 4.2 4.0

females 9.8 6.4 3.0 2.0

Audience

2 Situations

1) Examining a Between-Subject

independent variable at a

specific level of a Within-

Subjects variable

2) Examining a Within-Subjects

variable at a specific level

of a Between-Subjects

independent variable

8

when interaction- you want to make a

graph and then discribe it

the the 2 dots the same or

diff- simple main effect

What about gender

at the different levels of audience?

aud0 aud1 aud2 aud3

males 8.0 6.2 4.2 4.0

females 9.8 6.4 3.0 2.0

aud0 aud1 aud2 aud3

males 8.0 6.2 4.2 4.0

females 9.8 6.4 3.0 2.0

aud0 aud1 aud2 aud3

males 8.0 6.2 4.2 4.0

females 9.8 6.4 3.0 2.0

aud0 aud1 aud2 aud3

males 8.0 6.2 4.2 4.0

females 9.8 6.4 3.0 2.0

9

0

2

4

6

8

10

Mean number of nosepicks

0 1 2 3

Audience

Gender by Audience Interaction

Women

Men

Interested in: Effect of gender at the different levels of audience

10

aud0: F(?, ?) = ?? / ??

aud1: F(?, ?) = ?? / ??

aud2: F(?, ?) = ?? / ??

aud3: F(?, ?) = ?? / ??

aud0 aud1 aud2 aud3

males 8.0 6.2 4.2 4.0

females 9.8 6.4 3.0 2.0

Calculate

4 F-ratios

11

aud0 aud1 aud2 aud3

males 8.0 6.2 4.2 4.0

females 9.8 6.4 3.0 2.0

aud0: F(?, ?) = ?? / ??

aud1: F(?, ?) = ?? / ??

aud2: F(?, ?) = ?? / ??

aud3: F(?, ?) = ?? / ??

Calculate

4 F-ratios

12

males to females- need an F

value for each - do by hand

df for num and den& the actual

num and den