Actor-Partner Interdependence Model

or APIM

David A. KennyUniversity 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 Y2

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

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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

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Person 1's

Quality of Life

APIM Diagram

Person 2's

Quality of Life

Actor for Person 1

Actor for Person 2

Partner

from 1 to 2Partn

er

from 2 to

1

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."

Person 1's

Depression

Person 2's

Depression

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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

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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

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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

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UU Studies

• Health Promotion Studies

• Some Examples– 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

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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.

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UU, DU, and DD Studies• Some Examples

– 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 11

Not Discussed

• Distinguishability• Statistical estimation of the APIM• Actor-partner interactions• Over time studies• Alternative dyadic models

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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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Thank You!

http://davidakenny.net/doc/iarr_her.ppt 14