By Ralph L. Levine, Hiram E. Fitzgerald (auth.), Ralph L. Levine, Hiram E. Fitzgerald (eds.)
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Extra info for Analysis of Dynamic Psychological Systems: Volume 2 Methods and Applications
However, this approach does not readily give one an indication of the overall goodness of fit of the model, and the parameter estimates are sensitive to multicollinearity, the presence of strong relationships among explanatory variables (Dutta, 1975; Intriligator, 1978; Johnston, 1972). Multicollinearity is especially troublesome if one has tried to include all relevant causes of the endogenous variables to satisfy the condition of self-containment. The full-information or simultaneous estimation procedure as used in LISREL (Joreskog & Sorbom, 1983) and EQS (Bentler, 1989) is the other method for testing the hypothesized structural relationships reflected in the model.
Child Development. 58. 80-92. Hausman. J. A. (1977). Errors in variables in simultaneous equation models. Journal of Econometrics. 389-401. Hertzog. C.. & Nesselroade. J. R. (1987). Beyond autoregressive models: Some implications of the trait-state distinction for the structural modeling of developmental change. Child Development. 58. 93-109. Hsiao. C. (1976). Identification and estimation of simultaneous equation models with measurement error. International Economic Review. 319-339. Hunter. J.
To meet this condition, it is necessary to include all relevant causes of the endogenous variables included in the hypothesized model. A relevant cause is one that has at least a moderate and unique effect on an endogenous variable and is correlated with the other causes of that endogenous variable that have been included in the model. Failure to meet this condition results in biased estimates of the structural parameters because the effects of the unmeasured, relevant causes are included in the disturbance term for that equation (James, 1980).