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
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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
3
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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APIM Diagram
Person 1's
Actor for Person 1
Depression
Person 1's
Quality of Life
Person 2's
Person 2's
Depression
Actor for Person 2
Quality of Life
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."
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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
6
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.
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– Couple type as a moderator
Not Discussed
•
•
•
•
•
Distinguishability
Statistical estimation of the APIM
Actor-partner interactions
Over time studies
Alternative dyadic models
12
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)
13
Thank You!
http://davidakenny.net/doc/iarr_her.ppt
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