Mediation vs Moderation

Question 1

When a variable acts as a moderator, what does this mean?

Answer 1

​​​​​​That the effect of the IV on the DV depends on the values of another variable

Question 2

Does a moderator variable need to be categorical?

Answer 2

​​​​​​​No, moderators, can be either categorical or continuous

Question 3

According to Baron and Kenny, when is a moderator variable usually introduced?

Answer 3

​​​​​​​When there is a weak or inconsistent relationship

Question 4

Is the relationship between the moderator variable on the IV and DV always linear?

Answer 4

No, a moderator relationship can be linear, non-linear and stepped

Question 5

Is the following regression equation, which is the moderating variable: Y = c + d1x + d2z + d3xz + error

Answer 5

​​​​​​​d3xz

Question 6

Moderation tests a causal pathway?

Answer 6

​​​​​​​No, moderation does not test a causal pathway

Question 7

The equation for Moderation

Answer 7

Y = a + b₁x + b₂z + b₃xz

Question 8

A moderator variable is another word for:

Answer 8

Interaction variable

Question 9

What is centering?

Answer 9

​​​​​​​When every case for a variable is subtracted from a common value, usually the mean of the variable

Question 10

While there is debate about centering variables, when examining interactions what is one of the arguments for centering interaction variables?

Answer 10

Reduces problems associated with multicollinearity

Question 11

Does the method of interpreting the interaction change if other control variables are introduced into the regression model?

Answer 11

​​​​​​The interaction term is interpreted in the same way, however the beta coefficient may change

Question 12

What is meant when we use the term non-additivity?

Answer 12

That for different values of independent variables the relationship with the dependent variable and the moderator may differ?

Question 13

What is an effective way of trying to understand the non-addivity relationship of an interaction variable?

Answer 13

Plotting values of the interaction variable

Question 15

What utility can be used with SPSS to help plot interactions?

Answer 15

Process utility

Question 16

A plot of simple slopes with a significant interaction should have lines that are:

Answer 16

Slopes that are not parallel

Question 17

A mediation analyses is examining what?

Answer 17

A causal pathway, and whether there is and intervening variable between the IV and DV

Question 18

If using regression Baron and Kenny suggest how many regression models should be run:

Answer 18

Three: This tests the total effect, direct and indirect effect

Question 19

Using the Baron and Kenny approach, and the figures here, when is full mediation identified?

Answer 19

When c` is not significant and c was originally significant

Question 20

Using the Baron and Kenny approach, and the figures here, when is partial mediation identified?

Answer 20

When c` is reduced in magnitude compared to c

Question 21

Using the Baron and Kenny approach, and the figures here, when is no mediation?

Answer 21

When b is not significant

Question 22

What statistical program is used to test for mediation?

Answer 22

Mplus

Question 23

Must mediation analyses be done with only continuous variables?

Answer 23

No, the IV, MV and DV can be either binary or continuous

Question 24

When using SPSS to run a mediation analyses, what three key output results are produced?

Answer 24

Total effect (c), direct effect (c`); and indirect effect (a*b)

Question 25

Mediation can expressed in the following way:

Answer 25

total effect = direct effect + indirect effect

Question 26

Mathematically, mediation can also be expressed in the following way:

Answer 26

c = c’ + (a*b)

Question 27

Mediation effect sizes can be used to assess:

Answer 27

How much of the total effect is mediated

Question 28

According to Fergusson (2009), a moderate to large effect size is greater than:

Answer 28

>=.25

Question 30

Which of the following statements is correct?

• Factor analysis takes a small number of variables and combines into a large number of factors
• Confirmatory factor analysis allows us to test a proposed model about how variables relate to each other
• Whereas exploratory factor analysis uses dimensions/factors to explain shared variance among variables in the analysis, confirmatory factor analysis uses dimensions/factors to account for all variance (shared and unique) in the model
• Factor analysis suggests that two variables are related, but doesn’t propose a shared third-variable to explain this association

Answer 30

Confirmatory factor analysis allows us to test a proposed model about how variables relate to each other