week 4 - mediation

Question 1

what are the difference between means

Answer 1

• T-tests helps answer the question:
  “Is there a difference between two groups in performance on X?”
• ANOVA helps answer the question:
  “Is there a difference between two or more groups / factors in performance on X?”
• with a third variable we can see if this affects performance at different levels

Question 2

what is association

Answer 2

• what is the relationship between two variables

Question 3

what is a casual model of mediation

Answer 3

• “how does a predictor variable (X) influence/affect the outcome variable (Y)?
• We assume a third variable is involved
• The third variable is called the mediator (M)
• It is situated between the predictor (X) and outcome variable (Y)

Question 4

what are the parts of a mediation model

Answer 4

• X ________c________ Y
• path of total effect = c
• Mediated relationship
• mediator variable (M)
• path of indirect effect = ab
• a = X predicts M
• b = M predicts Y
• path of direct effect = c’
• ab + c’ = c = total effect of X on Y
• either partial or full mediation

Question 5

what are the conditions of a mediation model

Answer 5

• X need not be a significant predictor of Y
• M must not be a primary predictor variable
• M must not be any of the study conditions
• M must be dependent upon X
• M must reduce or eradicate the impact of X on Y

Question 6

what are the different types of mediation models

Answer 6

• partial - path of c’ is reduced but non-zero
• full - when path c/ is at 0

Question 7

what are the assumptions of linear models

Answer 7

• follows all the assumptions of a linear regression
• As an explanatory process, a predictor (X) can be said to be ‘causally’ related to the outcome (Y) when:
• x is associated with y
• x precedes changes in y
• no other unmeasured variables are related to x and also affect y

Question 8

what is desiderata

Answer 8

• x should/could precede m in time
• m should significantly predict y but y could also significantly predict m
• high power

Question 9

what is the method for the model

Answer 9

• test path of the total effect
• test significance of slope c
• linear regression of x on y
• test path of indirect effect a and b
• test significance of slope a and slope b in two independent models
• linear regression of m on y while controlling for x
• test if c’ < c
• significant c’ = partial mediation
• non significant c’ = full mediation

Question 10

what is the bootstrap test

Answer 10

• automated process
• resampling method for the indirect pathway using the model data with replacement
• average = indirect effect estimate
• generates confidence intervals also

Question 11

how do you report the results

Answer 11

• report the indirect effect and its confidence intervals
• report each pathway with either its significance value or confidence interval
• discuss additional assumptions of mediation analysis are met

Question 12

how do you interpreting results

Answer 12

• Benefits of a direct effect in the context of a significant indirect effect (partial mediation) – it informs theory development
• Size of the indirect effect indicates the strength of mediation
• Complementary – effects for both pathways are in the same direction
• Competitive – effects for both pathways are in opposite directions