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Using k to Estimate and Test Patterns in the APIM. David A. Kenny. You need to know the Actor Partner Interdependence Model and APIM patterns!. APIM. APIM Patterns. APIM Patterns. Couple Model Equal Actor and Partner Effects: a = p Contrast Model - PowerPoint PPT Presentation
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Using k to Estimate and Test Patterns in the APIM
David A. Kenny
February 17, 2013
You need to know the Actor Partner Interdependence Model and APIM patterns!
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APIM APIM Patterns
APIM Patterns• Couple Model
– Equal Actor and Partner Effects: a = p• Contrast Model
– Actor plus partner sums to zero: a – p = 0• Actor Only Model
– Partner effect is zero: p = 0• Partner Only Model
– Actor effect is zero: a = 0
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• Suggested by Kenny and Ledermann (2010) • k is the ratio of the partner effect to the actor
effect or p/a• k is named after Larry Kurdek, a pioneer in the
study of dyadic data• Special cases of k:
–k is 1, couple model–k equal to −1, contrast model–k equal to zero, actor-only model
The Parameter k
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-1 0 +1
Contrast Actor Only Couple a = -p p = 0 a = p
k5
-1 0 +1
Contrast Actor Only Couple a = -p p = 0 a = p
But k might equal 0.5.
k6
Phantom Variables• One way to estimate k is using a phantom
variable.• Phantom variable
– No conceptual meaning– Forces a constraint– Latent variable– No disturbance
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Standard APIM
X1
X2
Y1
Y2
E1
E2
1
1
a1
p21
p 12
a2
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Phantom Variables to Estimate k
• Now the indirect effect from X2 to Y1, p12 equals a1k1
• Thus, k1 = and k2 = and
X1
X2
Y1
Y2
E1
E2
1
1
a1
a2
P1
a1
k1
P2
a2
k2
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Estimates and Confidence Interval
• Use bootstrapping to obtain the asymmetric confidence interval (CI).
• Check to see if 1, -1, or 0 are in the CI of k.
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• Note that k is not defined when the actor effect is zero.
• Thus, k and its confidence interval should not be computed if the actor effect is small.
Caution in Computing the Parameter k
Distinguishability and k
• For distinguishable dyads, k may differ for the two members which might be theoretically interesting: e.g., wives couple model and husbands contrast model.
• Need to test to see if k varies across the distinguishing variable.
• Note that k may not vary, even if a and p vary by the distinguishing variable:
k = = 12
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ResultsDistinguishable
Wives: kW = 0.851 (0.223 to 2.038 )Husbands: kH = 0.616 (0.294 to 1.187)
Equal values of k kW = kH = 0.710 (0.489 to
0.989 )c2(1) = 0.320, p = .571
Indistinguishable: k = 0.719 (0.484 to 1.027)14
CI
Example SetupsAmos and Mplus (and soon laavan) setups can be downloaded at
davidakenny.net/papers/k_apim/k_apim.htm
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• When dyads are distinguishable, we previously took the two paths leading into Y to define k: k1X = and k2X =
• Alternatively k can be defined by the two paths coming from X:
k1X = and k2X = • For instance if one person is more “influential”
than the other, that person would have kX of 1 and the partner may have a kX of zero.
Defining k in Terms of X or kX
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X1
X2
Y1
Y2
E1
E2
1
1
a1
p21
p 12
a2
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X1
X2
Y1
Y2
E1
E2
1
1
a1
p21
p 12
a2
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• In some contexts the partner effect is larger than the actor effect, i.e., partner-only models.
• Note if a = 0, k = ∞! • In this case, it may make more sense to
define k as the ratio of the actor to the partner effect or kʹ =
Defining k in as Actor Effect Divided by Partner Effect
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ConclusionUsing k can simplify the model and link the model to theory.
ReadingKenny & Ledermann (2010), Journal of Family Psychology, 24, pp. 359-366.
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