Patterns of
Actor and Partner Effects
David A. Kenny
February 17, 2013
You need to know the Actor
Partner Interdependence
Model!
APIM
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APIM Patterns: Couple Model
• Model
– Equal actor and partner effects: a = p
– e.g., my depressive symptoms has the same
effect on my quality of life as does my
partner’s depressive symptoms on my quality
of life
• Average or sum as the predictor
– Although measured individually, the predictor
variable is a “dyadic” variable, not an
individual one
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APIM Patterns: Contrast
• Model
– Actor plus partner effects equals zero: a – p =
0
– Klumb et al. (2006): time spent doing
household labor on stress levels
• The more household labor I do, the more stressed
I feel.
• The more household labor my partner does, the
less stress I feel.
• Difference score (actor X minus partner X) as
the predictor
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APIM Patterns:
Actor or Partner Only
• Actor Only
– Actor present but no partner effect
– Fix the partner effect to zero.
• Partner Only
– Partner present but no partner effect
– Fix the actor effect to zero.
– Relatively rare.
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Testing Patterns
• Multilevel Modeling
– Sum and difference approach
• Structural Equation Modeling
– Setting coefficients equal
– Use of phantom variables
• General approach to patterns: k
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Sum and Difference
Approach
• Remove the actor and partner variables
from the model.
• Add to the model the Sum and the
Difference score as predictors.
• If Sum is present, but not the Difference,
you have a couple model.
• If Sum is not present, but the Difference is,
you have a contrast model.
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Acitelli Example
• Distinguishable
– Husbands
• Sum: 0.392, p < .001
• Difference: 0.131, p = .088
– Wives
• Sum: 0.373, p < .001
• Difference: 0.001, p = .986
• Indistinguishable
– Sum: 0.344, p < .001
– Difference: 0.056, p = .052
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Testing the Couple Model
Using SEM
• Actor effect equal to the partner effect.
• Can be done by setting paths equal.
• Distinguishable dyads
a1 = p12 and a2 = p21
• Indistinguishable dyads
a=p
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Acitelli Example
• Distinguishable
–Husbands: 0.346
–Wives: 0.347
–Test: c2(2) = 4.491, p = .106
• Indistinguishable
–Effect: 0.344
–Test: c2(1) = 3.803, p = .051
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Testing the Contrast
Model Using SEM
• Actor effect equal to the partner effect
times minus 1.
• Can be done by using a phantom variable.
• Phantom variable
– No conceptual meaning
– Forces a constraint
– Latent variable
– No disturbance
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Contrast Constraint Forced by
Phantom Variables (P1 and P2)
a1
X1
Y1
1
E
1
-1
a2
P1
a1
P2
-1
X2
a2
Y2
1
E2
• Now the indirect effect from X2 to Y1, p12
equals (-1)a1
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Acitelli Example
c2(2) = 69.791, p < .001
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Conclusion
Using patterns can link the APIM to theory
and simplify the model.
The k parameter is a general way to
measure and test patterns
Readings
pp. 147-149, in Dyadic Data Analysis by
Kenny, Kashy, and Cook
Kenny & Cook, (1999), Personal
Relationships, 6, pp. 433-448.
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