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Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

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Page 1: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 1

RStats Statistics and Research Camp 2014

Moderation and Mediation

Session 2

Todd Daniel PhDRStats Institute

Page 2: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 2

Page 3: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 3

“So far, we have been unable to document any incidents that were sparked by a cellular telephone. In fact, many researchers have tried to ignite fuel vapors with a cell phone and failed.”

Petroleum Equipment Institute

“The wireless industry has done studies on the potential for wireless phones to create sparks…there is no documented incident where the use of a wireless phone was found to cause a fire or explosion at a gas station.”

Federal Communications Commissionhttps://www.youtube.com/watch?v=AIlsJPNMQss

Page 4: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 4

Hmmmm…

• More gas station fires occur to women

• Women are more likely to re-enter the car

• Women are less likely to touch the car when exiting

• Conclusion: static electricity not cell phones

Isn’t this more useful?

Page 5: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 5

Stats Tell Us What?

Stats tell us what.

How? In what way?

By which pathway?

Under what circumstances? Grow from whether and if

to how and when

Page 6: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 6

Next Steps

• NHST tells us whether• Correlation and Regression tell us if• Mediation answers how• Moderation answers when

Page 7: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 7

Moderation

• The combined effect of two variables on another – Conceptually known as moderation– In statistical terms: an interaction

effect

Predictor Outcome

Moderator

Page 8: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 8

Example

• Do violent video games make teens aggressive?

• Participants– 442 youths

• IV: Number of hours spent playing video games per week

• DV: Aggression• Moderator: Callous

(unemotional) traits

Page 9: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 9

Conceptual moderation model

If callous traits are a moderator then the strength or direction of the

relationship between game playing and aggression is affected by callous

(unemotional) traits.

Game Playing

Aggression

Callous Traits

Page 10: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 10

Treating callous traits as categorical

Page 11: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

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Treating callous traits as continuous

Page 12: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 12

The Statistical Moderation Model

Predictor

OutcomeModerator

Predictor x Moderator

Page 13: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 13

Centering variables

• The interaction term makes the b’s for the main predictors uninterpretable in many situations

• For this reason, it is common to transform the predictors using grand mean centering

• Centering refers to the process of transforming a variable into deviations around a fixed point

Page 14: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 14

Output from moderation analysis

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Output from moderation analysis II

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Output from moderation analysis III

Page 17: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

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Following up Moderation with Simple Slopes analysis

Page 18: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 18

Simple slopes equations of the regression of aggression on video games at three levels of callous traits

Page 19: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 19

Reporting moderation analysis

Page 20: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

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How do I do that?

PROCESSwww.afhayes.comPlug in for SPSS

Page 21: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 21

Mediation Statistical Model

c'

Mediatora b

Predictor OutcomePredictor Outcomec

Simple RelationshipMediated Relationship

Mediation: when the relationship between a predictor variable and

outcome variable can be explained by their relationship to a third

variable (the mediator)

Page 22: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 22

Baron & Kenny, (1986)

• Mediation is tested through three regression models:1. Predicting the outcome from the

predictor variable2. Predicting the mediator from the

predictor variable3. Predicting the outcome from both

the predictor variable and the mediator

Page 23: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 23

Baron & Kenny, (1986)

Four conditions of mediation: 1. The predictor must significantly predict the

outcome variable.2. The predictor must significantly predict the

mediator.3. The mediator must significantly predict the

outcome variable.4. The predictor variable must predict the

outcome variable less strongly in model 3 than in model 1.

c'

Mediatora b

Predictor Outcome

Page 24: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 24

Limitations of Baron & Kenny’s (1986) Approach

• How much of a reduction in the relationship between the predictor and outcome is necessary to infer mediation? – people tend to look for a change in

significance, which can lead to the ‘all or nothing’ thinking that p-values encourage

Page 25: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 25

Sobel Test

• An alternative is to estimate the indirect effect and its significance using the Sobel Test (Sobel, 1982)

• If the Sobel test is significant, there is significant mediation

Page 26: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 26

Effect Sizes of Mediation Kappa-squared (k2)

(Preacher & Kelley, 2011)

Page 27: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 27

Example of a Mediation Model

Analysis is conducted in PROCESS

c'

Relationship Commitment

a b

Pornography Consumption Infidelity

Indirect Effect

Direct Effect

Page 28: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 28

Output from Mediation Analysis

Page 29: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

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Output from Mediation Analysis II

Page 30: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

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Output from Mediation Analysis III

Page 31: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

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Output from Mediation Analysis IV

Page 32: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

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Output from Mediation Analysis – Results of Sobel test

Page 33: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

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Reporting Mediation Analysis

There was a significant indirect effect of pornography consumption on infidelity though relationship commitment, b = 0.127, BCa CI [0.023, 0.335]. This represents a relatively small effect, κ2 = .041, 95% BCa CI [.008, .104].

Page 34: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 34

Reporting Mediation Analysis

Relationship Commitment

Pornography Consumption Infidelity

Direct Effect, b = 0.46, p = .02Indirect Effect, b = 0.13, 95% CI [0.02, 0.34]

Model of pornography consumption as a predictor of infidelity, mediated by relationship commitment. The confidence interval for the indirect effect is a BCa bootstrapped CI based on 1000 samples.

b = -0.47, p = .028 b = -0.27, p < .001

Page 35: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 35

Anything else?• You can do

mediation and moderation together

• Conditional Process Analysis

Page 36: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 36 Rees & Freeman, 2009

Self-Efficacy

Social SupportTask

Performance

Stress at Home

197 male amateur golfers

Page 37: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 37 Popan et al. (2010)

Typicality of Outgroup

Mbr.Attribution

Rationality of argument

Interaction w/ Outgroup

Attitude about Outgroup

Positive or Negative

Page 38: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 38 Parade et al. (2010)

Social anxiety

Parental Attachment Satisfaction

Satisfaction with Friends

172 female freshmen

Race

White v. Non-White

Page 39: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 39 Laran, Dalton, and Andrade (2011)

Persuasive Intent

Advertising Tactic

Willingness to Spend $

Behavioral Prime

Persuasion Focus

Awareness of advertising intent

Brand logos v. Brand logos + slogans

Was the advertisement intended to persuade

Slogan did (not) emphasize saving money

$0 to $500 on imaginary shopping spree

Page 40: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 40

Take a Break

Page 41: Slide 1 RStats Statistics and Research Camp 2014 Moderation and Mediation Session 2 Todd Daniel PhD RStats Institute

Slide 41

“Static electricity has caused fires at gas stations…for this reason, you should not re-enter your vehicle while you are refueling, since static electricity caused by friction from your clothing’s contact with the car seat can ignite the gas when you get back out of the car to complete the refueling process.”

Ohio State Bar Association website