1. University of Connecticut
IARR – Crete Modeling Nonindependence: The Actor-Partner Interdependence Model
3/27/2017
David A. Kenny
University of Connecticut
IARR 2006

2. Overview Model Three Brief Examples Estimation
Multilevel Modeling (SPSS)
Structural Equation Modeling (AMOS)

3. Between

4. Within

5. Mixed

6. Mixed Independent Variable
Definition
X does not equal X’ for all pairs
Or X + X’ equal the same value for every pair
Allows for the estimation of partner effects

7. Types of Dyads Definitions Distinguishable
Dyads with a categorical within-dyads variables that makes a difference
E. g., parent-child
Indistinguishable
Ordering of the two members is arbitrary
E.g. roommates
Whether dyads are distinguishable or not is matter of theoretical and statistical considerations.

8. Actor-Partner Interdependence ModelX Y
partner
partner
actor X' Y'

9. Types of APIM Models actor only a > 0; p = 0 partner only
couple model
a = p
social comparison model
a + p = 0

10. Example 1: Kraemer-Jacklin Study
Children in dyads are observed playing
Variables
X – Gender
X’ – Partner Gender
XX’ – Same vs. Opposite Gender
Y – Share toys with partner

11. APIM Effects Actor: Do girls share more than boys?
Yes, but the effect is small.
Partner: Do children share more when their partner is a girl?
Yes and the effect is twice as large as the actor effect.
Actor-Partner Interaction: Is there more
sharing with same-gendered partners?
Not much of a difference.

12. Example 2: Personality and Perceived of Control (Cook)
Siblings: one college student and one adolescent
Variables
Relative age (within dyads)
Assertiveness (mixed)
Cooperativeness (mixed)
Perceived Control (outcome variable)

13. Example 2: Results Gender: no effects Relative age
older seen as more powerful
Assertiveness
positive actor effect
negative partner effect
Cooperativeness
no actor effect
positive partner effect

14. Example 3: Perception of Romantic Partners: Measures and Sample
Both partners form a perception
A’s perception -- P(A)
Each guesses how his or her partner’s view
A’s guess of how B views the issue -- P(AB)
Probability Sample (Acitelli)
248 married couples
90 dating couples

15. Perception of Romantic Partners: Path Model
bias
P(A)
P(AB)
accuracy
accuracy
bias
P(BA)
P(B)

16. Perception of Romantic Partners: Conclusions
Few Gender Differences
Few Effects for Married vs. Dating
Accuracy and Bias for Each Measure
Strength of Effects Varies by Measure

17. Perception of Romantic Partners: Results

18. Dyadic Data Organization
Individual
One record for each individual
Only that individual’s data on the record
Dyad (useful for distinguishable dyads)
Each record one dyad
Different variables for each person
Pairwise (useful for indistinguishable dyads)
One record for each person
The person’s data and partner data included (each data point included twice)

19. Estimation Indistinguishable members Multilevel Modeling
Pairwise Data File
Illustrate with SPSS
Distinguishable members
Structural Equation Modeling
Dyad Data File
Illustrate with AMOS