5. Regression mediational and moderation

Question 1

What is the Baron and Kenny theory for?

Answer 1

Mediation

Question 2

What do you write (in a path diagram) on the regression pathway?

Answer 2

the b values

Question 3

What are the 4 steps to the Baron and Kenny model?

Answer 3

X on Y is sig. (SLR1)
X on M is sig. (SLR1)
M on Y is sig. (SMLR1)
But X on Y now not sig. (MLR1)

= full mediation

Question 4

How do you test for significance of mediation after running the Baron and Kenny analysis?

Answer 4

Use a Sobel Test

Question 5

What can you use to find the effect size of the mediation effect?

Answer 5

Haze Process Macros

Question 6

What is a direct effect?

Answer 6

When X effects Y (SLR)

Question 7

What is an indirect effect?

Answer 7

When X effects Y through M (MLR)

Question 8

What is the equation for the mediation line?

Answer 8

M = intercept + a*X + e

a being the b1 value for X

Question 9

What is the equation of the regression line where mediation is present?

Answer 9

Y = intercept + c’X + bM + e

where c’ is the b1 value for X on Y through M in a MLR and b is M on Y

Question 10

Which b values do you use in a regression line equation?

Answer 10

The unstandardised b values

Question 11

What are the 3 types of mediation?

Answer 11

Full
Partial
None

Question 12

What does a dotted line in a path diagram mean?

Answer 12

Non sig. effect

Question 13

When does partial mediation occur?

Answer 13

When the size of the p (sig. value) decreases but still remains sig. (so not full mediation)

Question 14

When does no mediation occur?

Answer 14

When the path a or b are not sig. or close to 0

Question 15

What is an exogenous variable?

Answer 15

Unrelated variables (e.g. no sig. effect… X predict Y and M predicts Y but X does not predict Y through M… e.g. no mediation)

Question 16

When you have exogenous variables you have….?

Answer 16

No mediation

Question 17

What is a spurious relationship?

Answer 17

Pearson r = sig.
But unstand. b value = 0
(no causal relationship)

Question 18

What type of multiple regression analysis do you do in the third step of the barron and kenny process?

Answer 18

Simultaneous

Question 19

What does the Adjusted R squared signify?

Answer 19

The percentage that accounts for the variance in the DV

Question 20

What happens if the F value is sig. in an ANOVA?

Answer 20

The regression equation using the IV is sig. better than using the mean of the IV to predict the DV

Question 21

What do F values compare in an ANOVA?

Answer 21

the mean and the model’s ability to predict the DV

Question 22

What do you find in the coefficients table?

Answer 22

The unstandardised b values

Question 23

What do the unstandardised b values tell us?

Answer 23

That when the IV increases by 1 point, the DV increased/ decreases by the b value*IV score

Question 24

The b values can be either?

Answer 24

Sig. or non sig increase/ decrease

Given by the t-values

Question 25

What are Cohen's conventions for r?

Answer 25

.1 .3 .5

Question 26

What are Cohen's conventions for r sq?

Answer 26

1% 9% 25%

Question 27

The adjusted R sq values (percentage of variance) can be either... which means?

Answer 27

Sig. or non sig. Given by F values (which means the model is either sig. or non sig. better than using the mean)

Question 28

When put in a hierarchical multiple regression what can we see?

Answer 28

How each variable contributes to the variance and whether that contribution has a sig. effect (whilst controlling for the other variables)

Question 29

What is the formula for the sobel test?

Answer 29

a path * b path / SE a*b paths

Question 30

What does the Haze Process Macro calculate?

Answer 30

The effect size (using the Confidence intervals using bootsrap)

Question 31

Why is it good to use Haze process macros?

Answer 31

It gives more power in smaller samples

Question 32

What is reported from Haze Macros output?

Answer 32

The Preacher and Kelly Kappa (K)

Question 33

What is the maximum possible value of effect size (Kappa)?

Answer 33

1

Question 34

How is Kappa intrepreted?

Answer 34

Cohen's conventions or r sq

Question 35

When is the indirect effect not genuine?

Answer 35

When confidence intervals of Kappa are -x and +x (include 0 point)

Question 36

When does an interaction effect occur?

Answer 36

When X has an effect on Y when Z is present (better than adding both X and Z to get Y)

Question 37

What is the interaction term also referred to?

Answer 37

The product term or The centred product term

Question 38

Why do we need to centre the product term?

Answer 38

So that the scales are balanced | to standardise metrics (both carry same impact)

Question 39

How do we centre a IV?

Answer 39

Standardise by: | IV - Mean of IV

Question 40

What type of multiple linear regression do you use when using an interaction term?

Answer 40

Hierarchical (Blocking)

Question 41

What term do you enter first into a hierarchical MLR when using an interaction term?

Answer 41

The normal IVS (then in block to the Interaction Term) IV1 and IV2 Then IV1*IV2

Question 42

What can you conclude if after doing a MLR using an Interaction effect, the interaction term is non sig.?

Answer 42

Then the additive (main) effect is best (Normal linear regression will do e.g. DV = b0 +bIV1 + bIV2 + e)

Question 43

What can you conclude if after doing a MLR using an Interaction effect, the interaction term is sig.?

Answer 43

Then predictors are synergistic (moderating each other)

Question 44

What does synergistic mean?

Answer 44

Moderating (working together)

Question 45

What are the df used when reporting F

Answer 45

``` Regression df Residual df (N - k) ```

Question 46

What are the df when reporting t?

Answer 46

Residual df | N - k