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Reinartz, Werner J.; Echambadi, Raj; Cin, Wynne W. – Multivariate Behavioral Research, 2002
Tested empirically the applicability of a method developed by S. Mattson for generating data on latent variables with controlled skewness and kurtosis of the observed variables. Monte Carlo simulation results suggest that Mattson's method appears to be a good approach to generate data with defined levels of skewness and kurtosis. (SLD)
Descriptors: Computer Simulation, Monte Carlo Methods, Structural Equation Models
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Raykov, Tenko; Penev, Spiridon – Structural Equation Modeling, 1998
Discusses the difference in noncentrality parameters of nested structural equation models and their utility in evaluating statistical power associated with the pertinent restriction test. Asymptotic confidence intervals for that difference are presented. These intervals represent a useful adjunct to goodness-of-fit indexes in assessing constraints…
Descriptors: Goodness of Fit, Power (Statistics), Structural Equation Models
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Bollen, Kenneth A.; Paxton, Pamela – Structural Equation Modeling, 1998
Provides a discussion of an alternative two-stage least squares (2SLS) technique to include interactions of latent variables in structural equation models. The method requires selection of instrumental variables, and rules for selection are presented. An empirical example and Statistical Analysis System programs are presented. (SLD)
Descriptors: Interaction, Least Squares Statistics, Selection, Structural Equation Models
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Scheines, Richard; Hoijtink, Herbert; Boomsma, Anne – Psychometrika, 1999
Explains how the Gibbs sampler can be applied to obtain a sample from the posterior distribution over the parameters of a structural equation model. Presents statistics to use to summarize marginal posterior densities and model checks using posterior predictive p-values. (SLD)
Descriptors: Bayesian Statistics, Estimation (Mathematics), Sampling, Structural Equation Models
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Raykov, Tenko; Marcoulides, George A. – Structural Equation Modeling, 2000
Outlines a method for comparing completely standardized solutions in multiple groups. The method is based on a correlation structure analysis of equal-size samples and uses the correlation distribution theory implemented in the structural equation modeling program RAMONA. (SLD)
Descriptors: Comparative Analysis, Correlation, Sample Size, Structural Equation Models
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Yuan, Ke-Hai; Bentler, Peter M. – Psychometrika, 2000
Adapts robust schemes to mean and covariance structures, providing an iteratively reweighted least squares approach to robust structural equation modeling. Each case is weighted according to its distance, based on first and second order moments. Test statistics and standard error estimators are given. (SLD)
Descriptors: Least Squares Statistics, Robustness (Statistics), Structural Equation Models
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Sager, Jeffrey K.; Griffeth, Rodger W.; Hom, Peter W. – Journal of Vocational Behavior, 1998
Structural equation modeling was used to test the discriminant validity of three cognitions--thinking of quitting, intent to search, and intent to leave--in 242 sales workers. Results demonstrating a different relationship among the three cognitions were used to revise a 1977 model. (SK)
Descriptors: Intention, Labor Turnover, Sales Occupations, Structural Equation Models
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Lee, Sik-Yum; Shi, Jian-Qing – Structural Equation Modeling, 2000
Extends the LISREL model to incorporate fixed covariates at both the measurement and the structural equations of the model, establishing a Bayesian procedure with conjugate type prior distributions. Illustrates the efficiency of the algorithm and presents a goodness of fit statistic for assessing the proposed model. (SLD)
Descriptors: Bayesian Statistics, Goodness of Fit, Structural Equation Models
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Boomsma, Anne – Structural Equation Modeling, 2000
Provides advice on writing a research paper when structural equation models are being used in empirical work. Focuses on what information should be reported and what can be deleted without much loss of judgment about the quality of the research and validity of conclusions. (SLD)
Descriptors: Research Reports, Structural Equation Models, Technical Writing, Validity
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Ghisletta, Paolo; McArdle, John J. – Structural Equation Modeling, 2001
Describes some applications of latent growth curve models in the context of structural equation modeling using data from P. Trickett and F. Putnam (1993) on the physical height of abused (n=77) and nonabused (n=75) adolescent girls. Presents power calculations for the ability of the different models to discern the growth of the abuse sample from…
Descriptors: Adolescents, Child Abuse, Females, Height
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Ogasawara, Haruhiko – Structural Equation Modeling, 2001
Derives approximations to the distributions of goodness-of-fit indexes in structural equation modeling with the assumption of multivariate normality and slight misspecification of models. Also derives an approximation to the asymptotic covariance matrix for the fit indexes by using the delta method and develops approximations to the densities of…
Descriptors: Goodness of Fit, Statistical Distributions, Structural Equation Models
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Wen, Zhonglin; Marsh, Herbert W.; Hau, Kit-Tai – Structural Equation Modeling, 2002
Points out two concerns with recent research by F. Li and others (2000) and T. Duncan and others (1999) that extended the structural equation model of latent interactions developed by K. Joreskog and F. Yang (1996) to latent growth modeling. Used mathematical derivation and a comparison of alternative models fitted to simulated data to develop a…
Descriptors: Goodness of Fit, Interaction, Simulation, Structural Equation Models
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Raykov, Tenko – Applied Psychological Measurement, 1999
Suggests that modeling change on the latent dimensions of interest is a better approach to measuring change than focusing on observed change scores and their properties. Discusses a latent-variable modeling approach that focuses on ability-change scores to permit estimation of individual latent-change scores and the relationship of ability-change…
Descriptors: Ability, Change, Measurement Techniques, Models
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Raykov, Tenko – Applied Psychological Measurement, 1997
Describes a structural equation model that permits estimation of the reliability index and coefficient of a composite index for congeneric measures. The method is also helpful in exploring the factorial structure of an item set, and its use in scale reliability estimation and development is illustrated. (SLD)
Descriptors: Estimation (Mathematics), Reliability, Structural Equation Models, Test Construction
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Sigfusdottir, Inga-Dora; Farkas, George; Silver, Eric – Journal of Youth and Adolescence, 2004
Drawing on R. Agnew's (Foundation for a general strain theory of crime and delinquency. Criminology 30: 47-87, 1992) general strain theory, this paper examines whether depressed mood and anger mediate the effects of family conflict on delinquency. We examine data on 7,758 students, 14-16 years old, attending the compulsory 9th and 10th grades of…
Descriptors: Structural Equation Models, Delinquency, Conflict, Adolescents
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