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

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

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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

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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.

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Actor-Partner Interdependence Model

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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

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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

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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.

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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)

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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

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

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Perception of Romantic Partners: Path Model

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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

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Perception of Romantic Partners: Results

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

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

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