Patterns of Actor and Partner Effects David A. Kenny

You need to know the Actor Partner Interdependence Model! APIM

APIM Patterns: Couple 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

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

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.

Testing Patterns Multilevel Modeling Structural Equation Modeling Sum and difference approach Structural Equation Modeling Setting coefficients equal Use of phantom variables General approach to patterns: k

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.

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

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

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

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

Contrast Constraint Forced by Phantom Variables (P1 and P2) X1 a1 Y1 1 E1 -1 a2 P1 a1 P2 -1 X2 Y2 1 E2 a2 Now the indirect effect from X2 to Y1, p12 equals (-1)a1

Acitelli Example c2(2) = 69.791, p < .001

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.