Richard Gonzalez
Center Director, Research Center for Group Dynamics, Institute for Social Research
Director, BioSocial Methods Collaborative, RCGD
Amos N Tversky Collegiate Professor, Psychology and Statistics, LSA
Professor of Marketing, Stephen M Ross School of Business
Professor of Integrative Systems and Design, College of Engineering
| E-mail: | Email Richard Gonzalez |
| Address: | Research Center for Group Dynamics Institute for Social Research University of Michigan 426 Thompson Street Ann Arbor, Michigan 48106 |
| Phone: | 734-647-6785 |
Data analysis for distinguishable dyads
In this paper we present methods for the analysis of dyadic data when the two members are distinguishable (e.g., gender distinguishes the members in a heterosexual couple). We develop the pairwise model for the distinguishable case and show that it provides identical parameter estimates as a latent level model in a structural equations model framework.
Gonzalez, R \& Griffin, D. (1999). The correlation analysis of dyad-level data in the distinguishable case. {\em Personal Relationships, 6,} 449-469. \doi{10.1111/j.1475-6811.1999.tb00203.x}
Abstract
Many theories of interpersonal relationships distinguish between individual-level processes and dyadic or group-level processes. This suggests that two-person relationships should be studied at the level of the dyad as well as at the level of the individual. We discuss correlational methods for dyads when each dyad contains two different types of individuals (e.g., a husband and wife, a mother and child, or an expert and a novice). In such dyadic interaction designs, the dyad members are said to be distinguishable. We present a method for computing the overall correlation for distinguishable dyads, and we discuss a model for separating the dyad-level and individual-level components of such a correlation. The computational techniques and their interpretation are described using data from 98 heterosexual couples.
