An Overview of the Logic and Rationale of Hierarchical Linear Models

Due to the inherently hierarchical nature of organizations, data collected in organizations consist of nested entities. More specifically, individuals are nested in work groups, work groups are nested in departments, departments are nested in organizations, and organizations are nested in environmen...

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Bibliographic Details
Published in:Journal of management 1997-11, Vol.23 (6), p.723-744
Main Author: Hofmann, David A.
Format: Article
Language:English
Subjects:
Data analysis
Hierarchies
Influence
Linear models (Statistics)
Linear regression models
Mathematical models
Methods
Organization theory
Organizational research
Organizational structure
Researchers
Social hierarchies
Statistical analysis
Variables
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Summary:Due to the inherently hierarchical nature of organizations, data collected in organizations consist of nested entities. More specifically, individuals are nested in work groups, work groups are nested in departments, departments are nested in organizations, and organizations are nested in environments. Hierarchical linear models provide a conceptual and statistical mechanism for investigating and drawing conclusions regarding the influence of phenomena at different levels of analysis. This introductory paper: (a) discusses the logic and rationale of hierarchical linear models, (b) presents a conceptual description of the estimation strategy, and (c) using a hypothetical set of research questions, provides an overview of a typical series of multi-level models that might be investigated.
ISSN:0149-2063
1557-1211
DOI:10.1177/014920639702300602