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Social Relations Model:Multiple Variables
David A. Kenny
Types of Variables in SRM Studies
• Dyadic variable
• Personality variable–Self variable
• Group variable
Multiple Dyadic Variables
Bivariate Correlations4 at the individual level2 at the dyadic level
Dyadic Variables
Individual-level CorrelationsActor-ActorActor-PartnerPartner-ActorPartner-Partner
Actor-Actor Correlation
If initially a person sees others as Extroverted, does that person still see others as extroverted after interacting with them?
Not really: r = .21
Actor-Partner Correlation
If initially a person sees others as Extroverted, is that person seen as extroverted after interacting with him or her?
Maybe: r = .46
Partner-Actor Correlation
If a person is initially seen by others as Extroverted, does that person see others as extroverted after interacting with them?
Not really: r = -.02
Partner-Partner Correlation
If initially a person is seen by others as Extroverted, is that seen as Extroverted after interacting with him or her?
Yes: r = .89
Relationship IntrapersonalIf one person, A, initially thinks
another person, B, is particularly extroverted, does A still think that B is particularly extroverted after interacting with him or her?
Nor really: r = .23).
Relationship InterpersonalIf one person, A, initially thinks
another person, B, is particularly extroverted, does B think that A is particularly extroverted after interacting with him or her?
Not really: r = -.15
Creating a Construct
Why?to separate error from
relationship variance
Multiple MeasuresSame measure at different
times.Different measures at the
same time.
How?Sum or average the scores.Create a construct or a latent
variable.
Stable versus Unstable Variance
stable variance: variance that correlates across different measures of the construct
unstable variance: variance that is unique to the specific measure of the construct
Measurement Model
Equal loadings of the different measures: All measures need to have the same units.
Equal unstable variance in each measure
Construct Variances
Stable ActorUnstable ActorStable PartnerUnstable PartnerStable RelationshipUnstable Relationship
Error VarianceVery often Unstable Actor and Partner
variances are very small.There is only Unstable Relationship
variance.Can report error variance as the sum of
Unstable Actor, Partner, and Relationship variances.
ExampleLiking at Two Times (Curry)
Stable UnstableActor .160 .029Partner .259 .016Relationship .422 .114
Error .159
Correlated Error
Some times, pairs of indicators share method variance.
Same timeSame instrument
Need to remove correlated error effect in computing correlations between two constructs.
A Personality
Variable with
a Dyadic Variable
Extroversion (personality variable) with Smiling (dyadic
variable)Actor Personality Variable
Correlation: If Dave is extroverted, does Dave smile more?
Partner Personality Variable Correlation: If Dave is extroverted, do others smile more at Dave?
A Personality Variable at the
Relationship LevelCompute the product of actor’s
personality X partner’s personality (both centered) or alternatively the absolute difference.
Correlate with relationship effect.
Self Variable as a Special Personality
VariableSelf Variable: A “dyadic”
measurement in which actor and partner are the same person.
Can correlated with actor and partner effects.
Group VariableSame score for all group members.Examples
genderexperimental condition
Testslevelvariances
Suggested Readings
Dyadic Data Analysis, Kenny, Kashy, & Cook, Chapter 8
Appendix B in Kenny’s Interpersonal Perception (1994)
Thank You!