IARR – Crete Modeling Nonindependence: The Actor-Partner Interdependence Model

1. IARR – CreteModeling Nonindependence: The Actor-Partner Interdependence Model David A. Kenny University of Connecticut http://davidakenny.net/dyad.htm

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

3. Between

4. Within

5. Mixed

6. 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 Mixed Independent Variable

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 Model actor X Y partner partner actor X' Y'

9. Types of APIM Models • actor only • a > 0; p = 0 • partner only • p > 0; a = 0 • 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. 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 Example 3: Perception of Romantic Partners: Measures and Sample

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