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Abstract

When one gathers dyadic data, one is very often faced with the burdensome task of restructuring the data. For instance, the use of multiple regression analysis or structural equation modeling (SEM) requires one type of data structure, whereas multilevel modeling or multilevel SEM usually requires a different data structure. However, data are often entered in neither of these structures. In this article, we first describe the most typical dyadic data formats, what format the major data-analytic methods require, and then present a toolbox called restructure and describe dyadic data (RDDD) with programs that restructure dyadic data from one format into another. Moreover, the programs identify different types of dyadic variables and provide descriptive and inferential statistics that can be informative to dyadic researchers. The programs, written in R, provide a graphical user interface and are designed to work with minimal input information that is much less than standard restructuring procedures.

Keywords

Data structures descriptive statistics dyadic data inferential statistics program R restructuring

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A toolbox with programs to restructure and describe dyadic data

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