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# Patterns of Actor and Partner Effects - PowerPoint PPT Presentation

Patterns of Actor and Partner Effects. David A. Kenny. You need to know the Actor Partner Interdependence Model!. APIM. APIM Patterns: Couple Model. Model Equal actor and partner effects: a = p

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Patterns of Actor and Partner Effects

David A. Kenny

• 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

• 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

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.

• Multilevel Modeling

• Sum and difference approach

• Structural Equation Modeling

• Setting coefficients equal

• Use of phantom variables

• General approach to patterns: k

Sum and DifferenceApproach

• 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.

• 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

Testing the Couple Model Using SEM

• Actor effect equal to the partner effect.

• Can be done by setting paths equal.

a1 = p12 and a2 = p21

a = p

• 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

• 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

• Now the indirect effect from X2 to Y1, p12 equals (-1)a1

X1

a1

Y1

1

E1

-1

a2

P1

a1

P2

-1

X2

Y2

1

E2

a2

c2(2) = 69.791, p < .001

Using patterns can link the APIM to theory and simplify the model.

The k parameter is a general way to measure and test patterns