miercuri, 4 august 2010

An overview of the logic and rationale of hierarchical linear models - A Special Issue: Focus on Hierarchical Linear Modeling

Hierarchically ordered systems are an integral and defining aspect of organizations. For example, Hall (1987) defined organizations as follows:
An organization is a collectivity with a relatively identifiable boundary, a normative order, ranks of authority, communication systems, and membership-coordinating systems; this collectivity exists on a relatively continuous basis in an environment and engages in activities that are usually related to a set of goals; the activities have outcomes for organizational members, the organization itself, and for society. (p. 40).
Even in this broad definition, a hierarchical ordering is evident. Individuals are organized into a collective that exists in an environment thereby resulting in three hierarchical levels: individual, collective/organization, and environment. Although these three levels would exist for any organizational investigation, there are likely to be several intermediate hierarchical levels. For example, a typical organization may have individuals nested within work groups, work groups nested in departments, departments nested in organizations, and organizations nested in environments. To investigate these various levels, one must measure variables and constructs that describe each of these levels.
How to investigate hierarchically ordered systems, such as organizations, has been a concern for a number of disciplines for quite some time. For example, researchers in sociology (e.g., Blalock, 1984; Mason, Wong & Entwistle, 1983), economics (e.g., Hanushek, 1974; Saxonhouse, 1976), education (Burstein, 1980), biology (e.g., Laird & Ware, 1982), marketing (e.g., Wittink,
1977), statistics (e.g., Longford, 1989), and management/organizational behavior (e.g., Mossholder & Bedeian, 1983) have all discussed issues, problems, and solutions surrounding research conducted within hierarchically ordered systems. From an organizational science perspective, two themes have dominated the discussion: (a) issues surrounding the aggregation of data, and (b) how to investigate relationships between variables residing at different hierarchical levels.

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