1. Dyadic Analysis: Using HLM
David A. Kenny
University of Connecticut /

2. Types of Dyads Definitions Distinguishable
Dyads with a categorical within-dyads variables that makes a difference
e. g., parent-child
Indistinguishable
Ordering of the two members is arbitrary
e.g. roommates
Whether dyads are distinguishable or not is matter of theoretical and statistical considerations.

3. Nonindependence: Definition
Degree of greater similarity (or dissimilarity) between linked observations versus unlinked observations
Nonindependence as the correlation between linked observations.

4. Negative Nonindependence
Two scores from the same dyad are more dissimilar than two scores from different groups.
How?

5. Compensation: If one person has a large score, the other person lowers his or her score. For example, if one person acts very friendly, the partner may distance him or herself,
Social comparison: The members of the dyad use the relative difference on some measure to determine some other variable. For instance, satisfaction after a tennis match is determined by the score of that match.
Zero-sum: The sum of two scores is the same for each dyad. For instance, the two members divide a reward that is the same for all dyads.
Division of labor: Dyad members assign one member to do one task and the other member to do another. For instance, the amount of housework done in the household may be negatively correlated.

6. Dyadic Designs Standard Each person has one partner
Social Relations Model (SRM) Designs
Each person has many partners, and each partner paired with many persons
One-with-Many
Each person has many partners, but each partner is paired with only one person

7. Standard Design

8. *
One-with-Many Design *

9. *
SRM Designs *

10. Remaining part of the presentation focuses on the standard design which is used in most dyadic studies.

11. Dyadic Data Organization
Individual
One record for each individual
Only that individual’s data on the record
Dyad (useful for distinguishable dyads)
Each record one dyad
Different variables for each person
Pairwise (useful for distinguishable dyads)
One record for each person
The person’s data and partner data included (each data point included twice)

12. Pairwise Data Organization
Dyad Number
Member Number
The Person’s Data
Partner’s Data
Acitelli Example

13. Types of Variables Between Dyads – Level Two Within Dyads
Both members have the same score
X = X′
Within Dyads
Sum of two scores a constant
X + X′ = c for all dyads

14. Between

15. Within

16. Mixed Variables Variables that vary within and between groups Examples
Most outcomes (and mediators)
Individual differences (e.g., personality)

17. Mixed

18. Gender and the Three Types
Between
Gay and Lesbian Couples
Within
Heterosexual Married Couples
Mixed
Friends

19. Actor-Partner Interdependence ModelX Y
partner
partner
actor X' Y'

20. Types of APIM Models actor only a > 0; p = 0 partner only
couple model
a = p
social comparison model
a + p = 0

21. Actor-Partner Interaction
Partner effect depends on the level of the actor effect
More than one way to test
A Level 2 Variable

22. Measurement of the Actor-Partner Interaction
Standard Product Approach (XX’) – make sure variables centered
Discrepancy Score (│X – X′│) (Absolute Difference)
Similarity – Negative Coefficient
Dissimilarity – Positive Coefficient
Higher Score of the Two [Max(X,X′)] – “It Takes Two”
Lower Score [Min(X,X′)] – “One of Us Can Drag Us Both Down”

23. Estimation Indistinguishable Members Multilevel Modeling
Pairwise Data File
Illustrate with HLM
Distinguishable Members
Structural Equation Modeling
Dyad Data File

24. Approaches Illustrated
Conventional Multilevel Model with Random Intercepts
Two-Intercept Model

25. Briefly Discussed One-with-many design
Standard design studied longitudinally