文档介绍：Volume 4, Article 7
August 2000
STRUCTURAL EQUATION MODELING
AND REGRESSION:
GUIDELINES FOR RESEARCH PRACTICE
David Gefen
Management Department
LeBow College of Business
Drexel University
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Detmar W. Straub
Department puter Information Systems
Robinson College of Business
ia State University
Marie-Claude Boudreau
Management Information System Department
Terry College of Business
University of ia
TUTORIAL
STRUCTURAL EQUATION MODELING
AND REGRESSION:
GUIDELINES FOR RESEARCH PRACTICE
David Gefen
Management Department
LeBow College of Business
Drexel University
Detmar W. Straub
Department puter Information Systems
Robinson College of Business
ia State University
Marie-Claude Boudreau
Management Information System Department
Terry College of Business
University of ia
ABSTRACT
The growing interest in Structured Equation Modeling (SEM) techniques
and recognition of their importance in IS research suggests the need pare
and contrast different types of SEM techniques so that research designs can be
appropriately selected. After assessing the extent to which these techniques are
currently being used in IS research, the article presents a running example which
analyzes the same dataset via three very different statistical techniques. It then
compares two classes of SEM: covariance-based SEM and partial-least-squares-
based SEM. Finally, the article discusses linear regression models and offers
guidelines as to when SEM techniques and when regression techniques should
be used. The article concludes with heuristics and rule of thumb thresholds to
guide practice, and a discussion of the extent to which practice is in accord with
these guidelines.
Communications of AIS Volume 4, Article 7 2
Structural Equation Modeling Techniques and Regression: Guidelines
For Research Practice by