Edited by Larry Dwyer, Alison Gill and Neelu Seetaram
5 Structural equation modeling Jenny (Jiyeon) Lee and Gerard Kyle NATURE OF STRUCTURAL EQUATION MODELING AND ITS EVOLUTION Structural equation modeling (SEM) is a tool for analysing multivariate data that has been long known in social sciences to be especially appropriate for theory testing (e.g., Bagozzi, 1980). It is also referred to as covariance structure analysis or covariance structure modeling. Structural equation models go beyond ordinary regression models to incorporate multiple independent and dependent variables as well as latent constructs that cluster the observed variables they are hypothesized to represent. They also provide a way to test a specified set of relationships among observed and latent variables as a whole, and allow theory testing even when experiments are not possible. As a result, these methods have become ubiquitous in all the social and behavioral sciences (e.g., MacCallum and Austin, 2000). With the advance of statistical software with graphical user interfaces, several “userfriendly” SEM programs have become accessible to tourism researchers (Kline, 2005). Of these, the most widely used programs are LISREL (Linear Structural Relationships), AMOS (Analysis of Moment Structures), EQS (Equations), Mplus, and PLS (Partial Least Squares). Each has idiosyncrasies and requirements for conducting analysis. These programs enable users to either choose to write code in syntax or use a graphical editor to generate the output by simply drawing the model. Over the past decade, these programs have also developed in conjunction with a plethora of introductory texts that provide insight on specific concepts, applications, and programming (e.g., LISREL (Byrne,...
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