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!