Module 2

Question 1

According to Dr Levesque what types of questions are moderation and mediation useful for?

Answer 1

• Moderation: Useful for When Questions
  
  • Under what conditions does X influence Y?
  • Explores the boundary conditions of associations
• Mediation: Useful for How/Why Questions
  
  • How does X influence Y?
  • Explores causal factors and mechanisms of associations

Question 2

What is Moderation?

Answer 2

• Moderation is a regression format of an interaction effect
  
  • Is the effect of X on Y moderated by M?
  • Note: M can also have a direct effect on Y
• Centering Variables: Continuous variables need to be mean centered to avoid multicollinearity
  
  • MC by subtracting the mean from the score (new mean = 0)
• Interaction Variables: Created by multiplying the MC scores

Question 3

What is Mediation?

Answer 3

• Examines how variables are causally related (also known as path analysis)
  
  • Size is measured using R² of the direct pathway compared to R² of the direct effect when M is included.
    
    • Partial vs Complete/perfect mediator
  • M is both an antecedent and consequent variable
  • In modern models paths a and c don’t need to be significant

Question 4

What is Simple Slopes Analysis?

Answer 4

• Simple Slopes Analysis provides information about the interaction effect in a moderation analysis
• Creates 3 regression lines for X - Y at low, mean, and high M values
  
  • Parallel = no interaction
  • If high M sharper slope than low M = M increases effect of X on Y
• In SPSS: Select conditioning -1SD, Mean, 1SD
  
  • Results found under “Conditional Effects of X on Y” section of output

Question 5

What is the difference between direct, total and indirect effects in a mediation analysis?

Answer 5

• Total Effect: Simple relationship between X and Y without M included in model
  
  • Represented by c
• Direct Effect of X on Y: Effect of X on Y when M is included in model
  
  • Represented by c’
• Indirect Effect of X on Y: Effect of X on Y via M
  
  • Product of a and b pathways
  • Product will be positive if a and b have same sign (even if both negative)
  • Significance tested using confidence interval (if includes 0 not significant)

Question 6

How do you run a moderation analysis in SPSS?

Answer 6

• Analysis -> Regression -> Process by Hayes
  
  • Model 1 = Moderation
  • Outcome = Y variable, Predictor = X variable, Moderator = Moderator W
  • Select HC3 (Davidson MacKinnon) for Heteroscadescity
  • Tick Generate Code, Mean Center
  • Select -1SD, Mean, 1SD for Conditioning and tick Johnson Neyman
• Interpreting Output
  
  • INT_1 = Interaction term - if this is significant then there is a moderation effect
  • Check whether confidence intervals include 0
  • Check Simple Slopes under Conditional effects

Question 7

How do you run a Mediation analysis through SPSS?

Answer 7

• Analyse -> Regression -> Process by Hayes
  
  • Model 4 - mediation
  • Outcome = Y variable, Predictor = X, Mediator = mediator
  • Tick Effect size, Pairwise, and Total Model
• Interpreting the output - is the indirect effect significant?
  
  • 1st model shows effect of predictor on mediator
  • 2nd model shows combined effect of predictor and mediator on outcome
  • Under Total, Direct and Indirect effects
    
    • Check indirect effect of X on Y -> if the BOOT confidence intervals do not include 0 it is significant

Question 8

How can you check for normality and missing data?

Answer 8

• Analyse -> Descriptives -> Frequencies
  
  • Will show you any missing data, range and sample size
• Analyse -> Descriptives -> Explore
  
  • Check Skewness and Kurtosis values
    
    • Close to 0 values indicate normality, positive = leptokurtic, +skew
  • Check Graphs of Normality
  • Finally check the Shapiro Wilk (significant value = not normal)
  • Make a educated judgement

Question 9

How do you check for outliers?

Answer 9

• Run a linear regression
  
  • Select Statistics, casewise diagnostics, MAH and Cook Distances
• Z-scores; Check for any z-score > 3SD
• Univariate: Check Casewise Diagnostics
  
  • If the table doesn’t appear there are no univariate outliers that need to be worried about
• Multivariate: Check Mah and Cook values against critical
  
  • Mah < 13 is good for 2 IVs (indicates no major outliers)
  • Cook < 1 indicates no one response is too influential

Question 10

How do you check for linearity, homoscedasticity, independence and multicollinearity?

Answer 10

• Run regression - select Dyan Watson, Collinearity, Zpre-Zresid plot, Normality PLot
• Zpred-Zresid Plot: assesses linearity and homescedascity
  
  • look for a random distribution
• Durbin Watson; assesses independence of errors
  
  • Value between 1-3 is good. Closer to 2 the better.
• Multicollinearity
  
  • Tolerance > 1 and VIF < 10 indicates no multicollinearity
  • Double check by verifying the correlations