Patterns of Actor and Partner Effects

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Patterns of Actor and Partner Effects David A. Kenny February 17, 2013

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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 - PowerPoint PPT Presentation

Transcript of Patterns of Actor and Partner Effects

Page 1: Patterns  of  Actor  and Partner  Effects

Patterns of Actor and Partner Effects

David A. Kenny

February 17, 2013

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You need to know the Actor Partner Interdependence

Model!

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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 predictor4

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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 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.

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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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X1

X2

Y1

Y2

E1

E2

1

1

a1

a2

P1

a1

-1

P2

a2

-1

Contrast Constraint Forced by Phantom Variables (P1 and P2)

• Now the indirect effect from X2 to Y1, p12 equals (-1)a1 12

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Acitelli Example

c2(2) = 69.791, p < .00113

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ConclusionUsing patterns can link the APIM to theory and simplify the model.The k parameter is a general way to measure and test patternsReadingspp. 147-149, in Dyadic Data Analysis by Kenny, Kashy, and CookKenny & Cook, (1999), Personal Relationships, 6, pp. 433-448.

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