Statistical Methods for Analyzing Family Interaction
William A. Griffin John M. Gottman University of Washington
As evidenced by this volume, investigators are extending their search for factors associated with the etiology and maintenance of depression and aggression beyond the individual, into the realm of interpersonal interaction. Obviously, the hope is that this focus on interpersonal rather than intrapersonal factors will reveal some consistent behavioral parameters that might help explain, and predict the emergence of these dysfunctional behaviors. By taking a social interactional perspective in analyzing aggression, depression, and marital conflict, this text implies that pathological behaviors are generated in the context of ongoing social interaction. Hence it is necessary to collect sequential data.
It is interesting to note that this social-interactional perspective, and its emphasis on sequential ordering, fully blossomed (in the scientific sense) only about 25 years ago with the work of Roger Barker and his colleagues ( 1963), and Harold Raush ( 1965). The analytic roots of this perspective, however, had been established earlier. In the late 1940s Shannon and Weaver ( 1949) introduced the concept that the information transmitted within a channel of communication could be quantified. This idea was immediately brought to the attention of psychologists by Miller and Frick ( 1949), and later by Attneave ( 1959). However, these writers focused on individuals, and not social interaction. Then in 1965, Stuart Altmann, an ethologist, published a classic paper on the stochastics of social communication. In this paper he developed the rationale for, and illustrated the use of, sequential contingencies as a means of gaining information (or reducing uncertainty) about the probable behaviors of social interactants. Although Altmann's paper addressed the communication patterns in rhesus monkeys, its application to any social group, including families, was quickly recognized. By the early 1970s, the concept of, and analysis for, sequential