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Bianconcini, Silvia – Multivariate Behavioral Research, 2012
In the SEM literature, simplex and latent growth models have always been considered competing approaches for the analysis of longitudinal data, even if they are strongly connected and both of specific importance. General dynamic models, which simultaneously estimate autoregressive structures and latent curves, have been recently proposed in the…
Descriptors: Structural Equation Models, Longitudinal Studies, Academic Achievement, Higher Education
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Schweizer, Karl – Multivariate Behavioral Research, 2011
The standardization of loadings gives a metric to the corresponding latent variable and thus scales the variance of this latent variable. By assigning an appropriately estimated weight to all the loadings on the same latent variable it can be achieved that the average squared loading is 1 as the result of standardization. As a consequence, there…
Descriptors: Structural Equation Models, Short Term Memory, Evaluation Methods, Comparative Analysis
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Beckstead, Jason W. – Multivariate Behavioral Research, 2012
The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…
Descriptors: Multiple Regression Analysis, Predictor Variables, Factor Analysis, Structural Equation Models
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Rozeboom, William W. – Multivariate Behavioral Research, 2009
The topic of this article is the interpretation of structural equation modeling (SEM) solutions. Its purpose is to augment structural modeling's metatheoretic resources while enhancing awareness of how problematic is the causal significance of SEM-parameter solutions. Part I focuses on the nonuniqueness and consequent dubious interpretability of…
Descriptors: Structural Equation Models, Equations (Mathematics), Matrices, Probability
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Gottfredson, Nisha C.; Panter, A. T.; Daye, Charles E.; Allen, Walter F.; Wightman, Linda F. – Multivariate Behavioral Research, 2009
Controversy surrounding the use of race-conscious admissions can be partially resolved with improved empirical knowledge of the effects of racial diversity in educational settings. We use a national sample of law students nested in 64 law schools to test the complex and largely untested theory regarding the effects of educational diversity on…
Descriptors: Law Students, Race, Law Schools, Structural Equation Models
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Nevitt, Jonathan; Hancock, Gregory R. – Multivariate Behavioral Research, 2004
Through Monte Carlo simulation, small sample methods for evaluating overall data-model fit in structural equation modeling were explored. Type I error behavior and power were examined using maximum likelihood (ML), Satorra-Bentler scaled and adjusted (SB; Satorra & Bentler, 1988, 1994), residual-based (Browne, 1984), and asymptotically…
Descriptors: Statistical Data, Sample Size, Monte Carlo Methods, Structural Equation Models