ABSTRACT
Over the past two decades, concerns in various fields with conceptual and methodological issues in conducting research with hierarchical (or clustered) data have led to the development of multilevel modeling techniques. For example, research on organizations presents opportunities to study phenomena in hierarchical settings. Individuals work in departments nested within particular organizations within geographic regions and countries. These individuals interact with their social contexts in a variety of ways. Individuals within successive clusters may share some common characteristics (e.g., socialization patterns, traditions and values, and beliefs about work). Similarly, the individuals nested in these various contexts may also influence the properties of the groups.
