Abstract
The most general structural equation models treated in this book are nothing more—and nothing less—than path analytical models (introduced in Chapter 1) that involve latent variables (discussed in Chapter 2). Even though classical path analysis has important advantages over conventional univariate or multivariate regression (e.g., the estimation of direct and indirect structural effects), one major disadvantage is that a priori hypothesized structures can be analyzed only under the usually unrealistic assumption that variables in the models are measured with no or negligible error. An integration of latent variables—as previously introduced in the context of confirmatory factor analysis—into path models relaxes this assumption and allows for the estimation of direct and indirect structural effects between variables or constructs that are not directly observable but, instead, are indicated by some imperfect observable measures.
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Recommended Readings
Nesselroade, J.R., and Cattell, R.B. (Eds.). (1988). Handbook of Multivariate Experimental Psychology (2nd ed.). New York: Plenum Press.
Pedhazur, E.J., and Schmelkin, L. (1991). Measurement, Design, and Analysis: An Integrated Approach. Hillsdale, NJ: Lawrence Erlbaum.
Thompson, B. (Ed.). (1989). Advances in Social Science Methodology (Vol. 1). Greenwich, CT: JAI Press.
Blalock, H.M. (1964). Causal Inferences in Nonexperimental Research. Chapel Hill: The University of North Carolina Press.
Blalock, H.M. (Ed.). (1985a). Causal Models in the Social Sciences (2nd ed.). New York: Aldine.
Blalock, H.M. (Ed.). (1985b). Causal Models in Panel and Experimental Designs. New York: Aldine.
Long, J.S. (1983b). Covariance Structure Models: An Introduction to LISREL. Beverly Hills, CA: Sage.
Bollen, K.A. (1989). Structural Equations with Latent Variables. New York: John Wiley & Sons.
Hayduk, L.A. (1987). Structural Equation Modeling with LISREL: Essentials and Advances. Baltimore: Johns Hopkins University Press.
Loehlin, J.C. (1992). Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
Bentler, P.M. (1993). EQS: Structural Equations Program Manual. Los Angeles: BMDP Statistical Software.
Bentler, P.M., and Wu, E.J.C. (1993). EQS/Windows: User’s Guide. Los Angeles: BMDP Statistical Software.
Jöreskog, K.G., and Sörbom, D. (1993a). LISREL 8 User’s Reference Guide. Chicago: Scientific Software International.
Jöreskog, K.G., and Sörbom, D. (1993b). LISREL 8: Structural Equation Modeling with the SIMPLIS Command Language. Chicago: Scientific Software.
Jöreskog, K.G., and Sörbom, D. (1993c). PRELIS 2: A Program for Multivariate Data Screening and Data Summarization: A Preprocessor for LISREL. Chicago: Scientific Software International.
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© 1996 Springer-Verlag New York, Inc.
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Mueller, R.O. (1996). General Structural Equation Modeling. In: Basic Principles of Structural Equation Modeling. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3974-1_3
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DOI: https://doi.org/10.1007/978-1-4612-3974-1_3
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-8455-0
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