The correlational analysis of dyad‐level data in the distinguishable case
Richard Gonzalez, Dale Griffin
Abstract
Richard Gonzalez, Dale Griffin
Abstract
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.
OpenAlex reports 142 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
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.
Key concepts: Dyad, Psychology, Interpersonal communication, Correlation, Interpretation (philosophy), Interpersonal interaction, Social psychology, Computer science