Actor-Partner Interdependence Model or APIM David A Actor-Partner Interdependence Model or APIM David A. Kenny University of Connecticut http://davidakenny.net/kenny.htm http://davidakenny.net/doc/iarr_her.ppt

APIM A model that simultaneously estimates the effects one's own characteristics and one's partner's characteristics on an outcome variable Data Requirements two variables, X and Y, and X causes or predicts Y Both members of the dyad have scores on X and Y

Actor Effect Definition: The effect of a person’s X variable on that person’s Y variable Example: the effect of one's depression on one's quality of life Both members of the dyad have an actor effect

Partner Effect Definition: The effect of a person’s partner’s X variable on the person’s Y variable Example: the effect of partner's depression on quality of life Both members of the dyad have a partner effect

APIM Diagram Person 1's Depression Person 1's Quality of Life Actor for Person 1 Person 1's Quality of Life Partner from 2 to 1 Partner from 1 to 2 Person 2's Depression Person 2's Quality of Life Actor for Person 2 The partner effect is fundamentally dyadic, but a common convention is to refer to it by the outcome variable. So "Partner from 2 to 1" would be called the "partner effect for person 1."

The APIM and Health Research Consider romantic couples Each member either diagnosed (D) or undiagnosed (U) Four major designs DU UU DD UU, DU, and DD

DU Studies: Some Examples Kim et al. (2008): the influence of psychological stress on life quality among mothers with cancer and their adult care giving daughters Hong et al. (2005): the association between the provision and receipt of social support in cardiac patients and their spouses   Mellon et al. (2007): factors associated with the fear of cancer-recurrence in cancer survivors and their caregivers Kershaw et al. (2008): effect of stress on coping in prostate cancer patients and their spouses Dorros et al. (2010): effect of depression on health in women with breast cancer and their partners

Key Questions in DU Studies Almost always there are mean differences on Y between D and U, but also important are differences in actor effects and especially between partner effects, i.e., measuring bidirectional influence. Important to test for asymmetry in: Y intercepts Actor effects Partner effects Error variances in Y

UU Studies Health Promotion Studies Some Examples Key question Dickerson & Kemeny (2004): effect of stress on cortisol levels Klumb et al. (2006): effect of housework on cortisol levels Butterfield & Lewis (2002): effect of tactics on health-related behaviors Key question Presence of partner effects

DD Studies Example: Knoll et al. (2009): Effects of stress on depression in couples undergoing assisted reproduction treatment. Key question: Partner effects Study would benefit by having a UU control group to see if effects are stronger or weaker in DD vs. UU couples.

UU, DU, and DD Studies Some Examples Key questions Hoff et al. (2009) conducted studies of gay men in which one, both, or neither member was HIV positive. McMahon et al. (2007) studied gay men where one member, both members, or neither member was diagnosed with hepatitis C. Key questions What is the effect of Disease on the behaviors and perceptions of person and their partner. Couple type as a moderator

Not Discussed Distinguishability Statistical estimation of the APIM Actor-partner interactions Over time studies Alternative dyadic models

APIM Work in Progress Testing Patterns Using k (Kenny & Lederman, 2010; Journal of Family Psychology) Mediation (Lederman, Macho, & Kenny, 2011; Structural Equation Modeling) Common Fate Model as an Alternative to the APIM (Lederman, & Kenny, under editorial review) Moderation (Garcia, Lederman, & Kenny, in preparation)

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