1. Restructuring Dyadic Data
David A. Kenny

2. Background
Dyadic Data Structures
Individual
One record for each person
Own person’s variables
Dyad
One record for the dyad
Both persons’ variables
Pairwise
View:

3. The Problem
You have one data structure and you want to convert to another.
individual to dyad
individual to pairwise
dyad to pairwise
Other conversions are trivial and can be accomplished either by deleting cases or renaming variables. 3

4. Dyad ID
For restructuring individual data, a unique identification number for each pair of persons is needed.
For longitudinal standard design, the “DyadID” is for each time point for each dyad. 4

5. Usual Strategies to Restructure
Restructuring by entering the data the “right” way.
Cut and paste
Computer programs
Built in routines to restructure
SPSS: davidakenny.net/webinars/powerpoints/Dyad/General/Restructuring.pdf

6. New Strategies to Restructure
R programs
Individual to pairwise
Individual to dyad
Dyad to pairwise
Apps
SPSS macro (no longer maintained)

7. R Restructuring Programs
Written in R
Co-written with Thomas Ledermann of Utah State University
Information available at

8. Details Installing R davidakenny.net/doc/InstallR.pdf Three programs
ItoP.R: Individual to pairwise
davidakenny.net/kkc/c1/ItoP.R
ItoD.R: Individual to dyad
DtoP.R: Dyad to pairwise
davidakenny.net/kkc/c1/DtoP.R

9. General R Program RDDD Description: davidakenny.net/doc/RDDD.pdf
Program: davidakenny.net/progs/RDDD.R

11. Descriptive Information for Dyad Dataset
Descriptive Information for Dyad Dataset
The dataset c:/ai.sav has been transformed from an individual to a dyad dataset called c:/dyad.csv. The distinguishing variable is Gender, and it has two levels, Wives (-1) and Husbands (1). There are 148 dyads and 296 individuals, 148 Wives and 148 Husbands. There are no missing data on any of the variables in the dataset.
There are 7 variables, 1 between-dyad variable, 1 within-dyad variable, and 5 mixed variables. The one between-dyad variable is Years Married, and the one within-dyads variable is Gender. The within-dyads variable, Gender, is a dichotomy and could be used as a distinguishing variable. The descriptive statistics for the variables as individuals are contained in Table 1 and the descriptive and inferential statistics as dyads are contained in Table 2.

12. Table 1: Descriptive Statistics for Individuals (All Variables)
Variable Mean sd Minimum Maximum Intra. r
Years Married
Gender
Self Positivity
Other Positivity
Satisfaction
Tension
Similar Hobbies

13.   Table 2: Inferential and Descriptive Statistics for Dyads (Mixed Variables)
Mean sd
Variable Wives Husbands p Wives Husbands p r p
Self Positivity <
Other Positivity
Satisfaction <.001
Tension <.001
Similar Hobbies < <.001
All calculations are based on 148 cases. Degrees of freedom for the test of mean difference are 147 and for the test of standard deviation difference and the test of the correlation are 146.

14. Restructuring Apps Uses the Ledermann & Kenny R programs
Adaptation to apps done with the assistance of Robert Ackerman
Web-based, no need to download R or to install R.
Answer prompts
Results
Text on the screen
Restructured data that can be downloaded
Link:

15. ItoP Illustration

19. SPSS Macros Steps Download the macro. Run the macro. Open the dataset.
Create the call.
Run the call.
Macros
pairwise.sps
indtodyad.sps

20. Calls (red is required)
pairwise.sps
Pairwise dyadid = dyad i1 = 'A' i2 = 'P' directory = 'c:\'.
indtodyad.sps
IndToDyad dyadid = dyad distvar = gender i1 = 'F' i2 = 'M' directory = 'c:\'.

21. Issues 2 records per dyad No string variables for most methods
The “Individual to Dyad” restructuring programs always produce a new variable called “partnum” (one member is given a “1” and the other a “2”) which can be useful in analyses.

22. Thomas Ledermann & Rob Ackerman!
Additional Readings
Kenny, D. A., Kashy, D. A., & Cook, W. L. Dyadic data analysis. New York: Guilford Press, Chapter 1.
Ledermann, T., & Kenny, D. A. (2014). A toolbox with programs to restructure and describe dyadic data. Journal of Social and Personal Relationships, online.
View as a webinar (small charge)
Special thanks to
Thomas Ledermann & Rob Ackerman! 22