Abstract
Though structural equation models today are usually associated with soft problems in the social sciences, they had their origin in the natural sciences—specifically biology. Europe’s nineteenth-century scholars were challenged to make sense of the diverse morphologies observed during an age of explorations, in Asia, Africa, and the Americas, as well as at home. In this period, new species of plants and animals were transplanted, domesticated, eaten, and bred at an unprecedented rate. An American ultimately provided one statistical tool that allowed scholars to build a science out of their diverse observations.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Anderson, C. A. (1983). The causal structure of situations: the generation of plausible causal attributions as a function of type of event situation. Journal of Experimental Social Psychology, 19(2), 185–203.
Anderson, T. W. (2005). Origins of the limited information maximum likelihood and two-stage least squares estimators. Journal of Econometrics, 127(1), 1–16.
Anderson, T. W., Kunitomo, N., & Matsushita, Y. (2010). On the asymptotic optimality of the LIML estimator with possibly many instruments. Journal of Econometrics, 157(2), 191–204.
Anderson, T. W., & Rubin, H. (1949). Estimation of the parameters of a single equation in a complete system of stochastic equations. Annals of Mathematical Statistics, 20(1), 46–63.
Anderson, T. W., & Rubin, H. (1950). The asymptotic properties of estimates of the parameters of a single equation in a complete system of stochastic equations. Annals of Mathematical Statistics, 21, 570–582.
Barabási, A.‐L., Dezső, Z., Ravasz, E., Yook, S.‐H., & Oltvai, Z. (2003). Scale-free and hierarchical structures in complex networks. Paper presented at the Modeling of Complex Systems: Seventh Granada Lectures.
Barabási, A. L., & Oltvai, Z. N. (2004). Network biology: understanding the cell’s functional organization. Nature Reviews Genetics, 5(2), 101–113.
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to causal modeling: personal computer adoption and use as an illustration. Technology Studies, 2(2), 285–309.
Basmann, R.L. (1988). Causality tests and observationally equivalent representations of econometric models. Journal of Econometrics 39(1), 69–104.
Browne, M. W., & Cudeck, R. (1989). Single sample cross-validation indices for covariance structures. Multivariate Behavioral Research, 24(4), 445–455.
Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230–258.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit (Sage focus editions, Vol. 154, p. 136). Thousand Oaks, CA: Sage.
Chin, W. W. (1998). Commentary: issues and opinion on structural equation modeling. MIS Quarterly, 22, vii.
Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. In Statistical strategies for small sample research (Vol. 2, pp. 307–342). Thousand Oaks, CA: Sage.
Christ, C. F. (1994). The Cowles Commission’s contributions to econometrics at Chicago, 1939–1955. Journal of Economic Literature, 32, 30–59.
Cowles, A. (1933). Can stock market forecasters forecast? Econometrica, 1, 309–324.
Cowles, A., 3rd, & Chapman, E. N. (1935). A statistical study of climate in relation to pulmonary tuberculosis. Journal of the American Statistical Association, 30(191), 517–536.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35, 982–1003.
Dhrymes, P. J. (1971a). Distributed lags. San Francisco, CA: Holden-Day Inc.
Dhrymes, P. J. (1971b). Equivalence of iterative Aitken and maximum likelihood estimators for a system of regression equations. Australian Economic Papers, 10(16), 20–24.
Dhrymes, P. J., Berner, R., & Cummins, D. (1974). A comparison of some limited information estimators for dynamic simultaneous equations models with autocorrelated errors. Econometrica, 42, 311–332.
Farebrother, R. W. (1999). Fitting linear relationships: a history of the calculus of observations 1750–1900. New York, NY: Springer.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50.
Freedman, D. A. (1987). As others see us: a case study in path analysis. Journal of Educational and Behavioral Statistics, 12(2), 101–128.
Gauss, K. F. (1809). Teoria motus corporum coelestium in sectionibus conicus solem ambientieum.
Goldberger, A. S., & Hauser, R. (1971). The treatment of unobservable variables in path analysis. Sociological Methodology, 3(8), 1.
Hood, W. C., Koopmans, T. C., & Cowles Commission for Research in Economics. (1953). Studies in econometric method (Vol. 14). New York, NY: Wiley.
Hotelling, H. (1936). Relations between two sets of variates. Biometrika, 28(3/4), 321–377.
Jöreskog, K. G. (1967). Some contributions to maximum likelihood factor analysis. Psychometrika, 32(4), 443–482.
Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Jöreskog, K. G. (1970). A general method for analysis of covariance structures. Biometrika, 57(2), 239–251.
Jöreskog, K. G., & Van Thillo, M. (1972). LISREL: a general computer program for estimating a linear structural equation system involving multiple indicators of unmeasured variables. ETS Research Bulletin Series, 1972, i–72.
Legendre, A. M. (1977). Note par M.*** Second supplement to the third edition of Legendre (1805). A separate pagination. English translation by Stigler. pp. 79–80.
Lohmöller, J. B. (1981). Pfadmodelle mit latenten variablen: LVPLSC ist eine leistungsfähige alternative zu LIDREL. München: Hochsch. d. Bundeswehr, Fachbereich Pädagogik.
Milgram, S. (1967). The small world problem. Psychology Today, 2(1), 60–67.
Quetelet, A. (1835). Sur l’homme et le développement de ses facultés ou essai de physique sociale. Bachelier, Paris.
Sargan, J. D. (1958). The estimation of economic relationships using instrumental variables. Econometrica, pp. 393–415.
Spearman, Charles, and Ll Wynn Jones. “Human ability.” (1950).
Stigler, S. M. (1981). Gauss and the invention of least squares. The Annals of Statistics, pp. 465–474.
Theil, H. (1953). Repeated least squares applied to complete equation systems. Central Planning Bureau, The Hague.
Theil, H. (1992). Estimation and simultaneous correlation in complete equation systems. Henri Theil’s contributions to economics and econometrics, pp. 65–107. Springer, Netherlands.
Theil, H. (1961). Economic forecasts and policy.
Tukey, J. W. (1954). Causation, regression, and path analysis. Statistics and Mathematics in Biology: 35–66.
Turner, M. E., & Stevens, C. D. (1959). The regression analysis of causal paths. Biometrics, 15(2), 236–258.
Werts, C. E., & Linn, R. L. (1970). Path analysis: psychological examples. Psychological Bulletin, 74(3), 193.
Werts, C. E., Linn, R. L., & Jöreskog, K. G. (1974). Intraclass reliability estimates: testing structural assumptions. Educational and Psychological Measurement, 34(1), 25–33.
Westland, J. C. (2010). Lower bounds on sample size in structural equation modeling. Electronic Commerce Research and Applications, 9(6), 476–487.
Wold, H. (1966). Estimation of principal components and related models by iterative least squares. Multivariate Analysis, 1, 391–420.
Wold, H. (1973). Nonlinear iterative partial least squares (NIPALS) modelling: some current developments. Multivariate Analysis, 3, 383–407.
Wold, H. (1974). Causal flows with latent variables: partings of the ways in the light of NIPALS modelling. European Economic Review, 5(1), 67–86.
Wold, H. (1975). Path models with latent variables: the NIPALS approach. New York, NY: Academic Press.
Wright, S. (1960). Path coefficients and path regressions: alternative or complementary concepts? Biometrics 16(2), 189–202.
Wright, S. (1920). The relative importance of heredity and environment in determining the piebald pattern of guinea-pigs. Proceedings of the National Academy of Sciences of the United States of America, 6(6), 320.
Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20(7), 557–585.
Wright, S. (1934). The method of path coefficients. Annals of Mathematical Statistics, 5(3), 161–215.
Wright, S. (1960). Path coefficients and path regressions: alternative or complentary concepts?. Biometrics 16(2), 189–202.
Zellner, A. (1962). An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American Statistical Association, 57, 348–368.
Zellner, A., & Theil, H. (1962). Three-stage least squares: simultaneous estimation of simultaneous equations. Econometrica, 30, 54–78.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Westland, J.C. (2015). A Brief History of Structural Equation Models. In: Structural Equation Models. Studies in Systems, Decision and Control, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-16507-3_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-16507-3_2
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16506-6
Online ISBN: 978-3-319-16507-3
eBook Packages: EngineeringEngineering (R0)