mediation: multiple variables david a. kenny. 2 mediation webinars four steps indirect effect causal...
TRANSCRIPT
Mediation: Multiple Variables
David A. Kenny
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Mediation Webinars
• Four Steps
• Indirect Effect
• Causal Assumptions
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The Mediational Model
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Multiple Xs• Consider two Xs.
– happens when X is categorical and there are more than two treatment groups
• Now two indirect effects of a1b and a2b (and two direct effects of c1
ʹ
and c1ʹ)
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Formative Variable
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Multiple Mediators• Consider two mediators, M1 and
M2,• Now two indirect effects a1b1 and
a2b2.• Can test:
–Is the sum different from zero?–Is each different from zero?–Is one larger than the other?
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Dual Mediation: Special Example of Two Mediators
• X has two levels
• Each level is intervention
• Both equally effective
• Each works through a different mechanism (i.e., mediator).
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Dual Mediation with No Intervention Effect
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Mediation with No Intervention Effect
Note that total effect of X on Y is .25 + (-.25) = 0! 9
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Causal Chains• One mediator causes another
X M1 M2 Y
• Indirect effect the product of three terms: ab1b2
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Multiple Outcomes• Consider two outcomes.
• Now two indirect effects ab1 and ab2.
• Consider combining outcome variables into a single variable, e.g., as a latent variables.
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X
U1
U2
MLatent
YLatent
M1
e1
1
1
M2
e21
M3
e31
Y1
e4
1
1
Y2
e51
Y3
e61
a b
c' 1
1
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Covariates• Often there are variables in the
analysis that need to be controlled:–Demographics–Baseline measures
• If a covariate interacts with X, it becomes a moderator.
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Why Add Covariates?• Causal Inference: Covariate
might be an omitted variable or a confounder.
• Power–If covariate is not correlated
with the predictor but with the outcome, it leads to an increase in power.
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Causal Assumptions• Generally assumed that
covariates only cause M and Y and are not caused by them.
• Covariates may cause or be caused by X, but that covariation is generally left unanalyzed.
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Same Covariates in Both the M and Y Equations?• Trim?• Sample size and number of
covariate issues.
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Thank You!