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Jongerling, Joran; Hamaker, Ellen L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article shows that the mean and covariance structure of the predetermined autoregressive latent trajectory (ALT) model are very flexible. As a result, the shape of the modeled growth curve can be quite different from what one might expect at first glance. This is illustrated with several numerical examples that show that, for example, a…
Descriptors: Statistics, Structural Equation Models, Scores, Predictor Variables
Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability
Raykov, Tenko; Penev, Spiridon – Structural Equation Modeling: A Multidisciplinary Journal, 2010
A latent variable analysis procedure for evaluation of reliability coefficients for 2-level models is outlined. The method provides point and interval estimates of group means' reliability, overall reliability of means, and conditional reliability. In addition, the approach can be used to test simple hypotheses about these parameters. The…
Descriptors: Reliability, Evaluation, Models, Intervals
Schochet, Peter Z.; Puma, Mike; Deke, John – National Center for Education Evaluation and Regional Assistance, 2014
This report summarizes the complex research literature on quantitative methods for assessing how impacts of educational interventions on instructional practices and student learning differ across students, educators, and schools. It also provides technical guidance about the use and interpretation of these methods. The research topics addressed…
Descriptors: Statistical Analysis, Evaluation Methods, Educational Research, Intervention
Flora, David B.; Curran, Patrick J.; Hussong, Andrea M.; Edwards, Michael C. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
A large literature emphasizes the importance of testing for measurement equivalence in scales that may be used as observed variables in structural equation modeling applications. When the same construct is measured across more than one developmental period, as in a longitudinal study, it can be especially critical to establish measurement…
Descriptors: Structural Equation Models, Item Response Theory, Measurement, Scores

Kaplan, David – Multivariate Behavioral Research, 1999
Proposes an extension of the propensity score adjustment method to the analysis of group differences on latent variable models. Uses multiple indicators-multiple causes (MIMIC) structural equation modeling to test hypotheses about treatment group differences. Discusses the role of factorial invariance as it relates to this approach. (SLD)
Descriptors: Groups, Hypothesis Testing, Scores, Structural Equation Models
Raykov, Tenko – Structural Equation Modeling: A Multidisciplinary Journal, 2006
A structural equation modeling based method is outlined that accomplishes interval estimation of individual optimal scores resulting from multiple-component measuring instruments evaluating single underlying latent dimensions. The procedure capitalizes on the linear combination of a prespecified set of measures that is associated with maximal…
Descriptors: Scores, Structural Equation Models, Reliability, Validity
Blackwell, Christopher W.; Kiehl, Ermalynn M. – Journal of LGBT Youth, 2008
This study examined registered nurses' overall attitudes and homophobia towards gays and lesbians in the workplace. Homophobia scores, represented by the Attitudes Toward Lesbians and Gay Men (ATLG) Scale, was the dependent variable. Overall homophobia scores were assessed among a randomized stratified sample of registered nurses licensed in the…
Descriptors: Structural Equation Models, Nurses, Statistical Analysis, Homosexuality
Capraro, Robert M.; Graham, James M. – 2002
This paper illustrates first how estimated Structural Equation Modeling (SEM) measurement error variances are actually estimates of score reliabilities. The major advantage of SEM over other analytic methods is that it accounts for measurement error. Score reliabilities are estimated as part of structural modeling, so that structural models test…
Descriptors: Error of Measurement, Estimation (Mathematics), Reliability, Scores

Dimitrov, Dimiter M.; Raykov, Tenko – Multivariate Behavioral Research, 2003
Presents a validation procedure for cognitive structures that is based on structural equation modeling of cognitive subordination relationships among test items. Illustrates the method using scores of 278 ninth graders on an algebra test and shows results for the same test when the linear logistic test model is used. (SLD)
Descriptors: High School Students, High Schools, Scores, Structural Equation Models

Raines-Eudy, Ruth – Structural Equation Modeling, 2000
Demonstrates empirically a structural equation modeling technique for group comparison of reliability and validity. Data, which are from a study of 495 mothers' attitudes toward pregnancy, have a one-factor measurement model and three sets of subpopulation comparisons. (SLD)
Descriptors: Factor Analysis, Factor Structure, Mothers, Parent Attitudes