Either target, rater, or even observation could be the unit of analysis. Independence of Units At the heart of statistical analysis is replication. For a replication to be a true replication, there must be independence of observations. Independence of observations is presumed in standard measures of variability. Common fate refers to the fact that sets of observations may have common causes.
Social interaction refers to direct and indirect influence between pairs of observations.
Using path analysis notation, a compositional effect is a curved line between observation, common fate is spuriousness, and social interaction is a direct effect. The degree of nonindependence can be viewed as a correlation coefficient, though it is not usually measured by an ordinary Pearson product-moment correlation. The Measurement of Nonindependence To determine the unit of analysis, an assessment of whether observations are independent is necessary. That is, the observations that are thought to be nonindependent, may in fact be independent. The measurement of nonindependence can be complicated, but in many cases an intraclass correlation can be used to measure the degree of nonindependence.