2 BackgroundDyadic Data StructuresIndividualOne record for each personOwn person’s variablesDyadOne record for the dyadBoth persons’ variablesPairwiseView:
3 The ProblemYou have one data structure and you want to convert to another.individual to dyadindividual to pairwisedyad to pairwiseOther conversions are trivial and can be accomplished either by deleting cases or renaming variables.3
4 Dyad IDFor 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 pasteComputer programsBuilt in routines to restructureSPSS: davidakenny.net/webinars/powerpoints/Dyad/General/Restructuring.pdf
6 New Strategies to Restructure R programsIndividual to pairwiseIndividual to dyadDyad to pairwiseAppsSPSS macro (no longer maintained)
7 R Restructuring Programs Written in RCo-written with Thomas Ledermann of Utah State UniversityInformation available at
8 Details Installing R davidakenny.net/doc/InstallR.pdf Three programs ItoP.R: Individual to pairwisedavidakenny.net/kkc/c1/ItoP.RItoD.R: Individual to dyadDtoP.R: Dyad to pairwisedavidakenny.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 DatasetThe 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. rYears MarriedGenderSelf PositivityOther PositivitySatisfactionTensionSimilar Hobbies
13 Table 2: Inferential and Descriptive Statistics for Dyads (Mixed Variables) Mean sdVariable Wives Husbands p Wives Husbands p r pSelf Positivity <Other PositivitySatisfaction <.001Tension <.001Similar Hobbies < <.001All 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 AckermanWeb-based, no need to download R or to install R.Answer promptsResultsText on the screenRestructured data that can be downloadedLink:
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 ReadingsKenny, 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 toThomas Ledermann & Rob Ackerman!22