Statistical Analysis of Discrete Relational Data

British Journal of Mathematical and Statistical Psychology (1986), 39, 41-64

24 Pages Posted: 19 Nov 2015 Last revised: 19 Feb 2016

See all articles by Stanley Wasserman

Stanley Wasserman

Indiana University Bloomington

Dawn Iacobucci

Vanderbilt University - Marketing; Vanderbilt University - Marketing

Date Written: 1986

Abstract

Social interaction data record the intensity of the relationship, or frequency of interaction, between two individual actors. Recent methods for analysing such data have treated these relational variables as continuous. A more appropriate method, described here, views these dyadic interactions as variables in multidimensional discrete cross-classified arrays, thus permitting analysis by log-linear models.

These methods extend previous approaches to social interaction data, which were limited to binary relations, by focusing on discrete-valued relations. Dyadic interactions, measured for a single discrete relational variable, are modelled stochastically using tendencies towards expansiveness (actor-effects), popularity (partner-effects) and reciprocity. Actor-characteristic variables may be used to group actors into a substantive partition, thus simplifying the analysis and subsequent interpretations.

Suggested Citation

Wasserman, Stanley and Iacobucci, Dawn and Iacobucci, Dawn, Statistical Analysis of Discrete Relational Data (1986). British Journal of Mathematical and Statistical Psychology (1986), 39, 41-64, Available at SSRN: https://ssrn.com/abstract=2691567 or http://dx.doi.org/10.2139/ssrn.2691567

Stanley Wasserman

Indiana University Bloomington ( email )

Dept of Biology
100 South Indiana Ave.
Bloomington, IN 47405
United States

Dawn Iacobucci (Contact Author)

Vanderbilt University - Marketing ( email )

Nashville, TN 37203
United States

Vanderbilt University - Marketing ( email )

Nashville, TN 37203
United States

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