Structural equation model

A Step-by-Step Approach to Using the SAS System for Factor Analysis and Structural Equation Modeling by Larry Hatcher... 

A biopsychosocial framework may reveal new links between physiological and psychological systems that, in turn, may provide new insights to guide future explorations that result in novel clinical or therapeutic treatments that relieve the burden of food allergy. Such a framework entails the adoption of methodologies that illuminate pathways in development such as qualitative methods and structural equation modeling. 

Kline, R. B. Principles and Practice of Structural Equation Modeling, 2nd ed. Guilford Press New York, 2004. 

FIG. 3. Structural equation model of data re-analysed from Nettelbeck Rabbitt (1992 = 98). A latent speed of processing factor mediates the effect of age on Performance IQ subtests. Fit statistics are as follows average off-diagonal standardized residuals = 0.02 chi square = 15.7 (df= 13), P = 0.26 Bentler-Bonett normed fit index = 0.95 Bentler-Bonett non-normed fit index = 0.99 comparative fit index = 0.99 all parameters are significant. 

Hayduk, L. A. Structural Equation Modeling with LISREL Essentials and Advances John Hopkins University Press Baltimore, 1987. 

Rosenstein, R. (1994), The Teamwork Components Model An Antdysis Using Structural Equation Modeling, Ph.D. dissertation. Old Dominion University. 

Note that in structural equation models measurable indicator variables are grouped into factors. These factors are unobservable/latent and influence latent/unobservable response variables. Such models are typically designed and estimated to confirm a theory about the construction and relations of the latent factors, see Pearl (2000). 

Multivariate techniques are required to assess multiple sources of variance. Yet, there has generally been a paucity of multivariate studies in experimental psychology (Harris, 1992). Multiple indicators of constructs have become salient due to increasing interest in structural equation modeling in biobehavioral research where multiple indicators are necessary to estimate latent variables and their associated error variance. In addition, the occasions dimension holds particular special significance for psychophysiology because most studies involve repeated measurements to some degree (Vasey Thayer, 1987). 

Lee, S. Y. Structural Equation Modelling A Bayesian Approach. John Wiley Sons, Inc., New York, NY, 2007. 

Brisa N. Sanchez is assistant professor in the Department of Biostatistics of the University of Michigan School of Pubhc Health. Her research interests are in statistical methods applicable to enviromnental and social epidemiology and health disparities. Her methodologic work involves developing robust fitting procedures and diagnostics for structural equation models and using the methods in applications to environmental health problems, such as in utero lead exposure and its effect on child development. Dr. Sanchez received her MS in statistics from the University of Texas at El Paso and her MSc and PhD in biostatistics from Harvard University. 

Hu, L. and Bender, P.M. 1999. Cutoff criteria for fit indexes in covariance stracture analysis Conventional criteria versus new alternatives. Structural Equation Modeling A Multidisciplinary Journal, 6(1), 1-55. 

Gerbing, D.W. and Hamilton, J.G. 1996. Viability of exploratory factor analysis as a precursor to confirmatory factor analysis. Structural Equation Modelling A Multidisciplinary Journal, 3, 62-72. 

Using a Structural Equations Modeling Apmroach to Design and 681... 

USING A STRUCTURAL EQUATIONS MODELING APPROACH TO DESIGN AND MONITOR STRATEGIC INTERNATIONAL FACILITY NETWORKS... 

Exhibit 16.1. Independent variables used for the structural equations model. 

We used sample products to build the structural equations model. Parameters for the numerical studies are shown in Table 16.1 and Exhibits 16.3 and 16.4. The costs and, in fact, the products themselves are meant to be roughly representative of a particular type of industry and not specifically representative of any actual company data. 

Exhibit 16.2. Dependent variables used for the structural equations model. Table 16.1. Products (Industries) Used in the computational studies... 

Table 16.3. Validation Results for the Structural Equations Model...

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