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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

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apim patterns couple model
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
apim patterns contrast
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
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
Testing Patterns
  • Multilevel Modeling
    • Sum and difference approach
  • Structural Equation Modeling
    • Setting coefficients equal
    • Use of phantom variables
  • General approach to patterns: k
sum and difference approach
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.
acitelli example
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
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 example1
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
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
slide12

Contrast Constraint Forced by Phantom Variables (P1 and P2)

  • 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

acitelli example2
Acitelli Example

c2(2) = 69.791, p < .001

conclusion
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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