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Raykov, Tenko – Applied Psychological Measurement, 1998
Proposes a method for obtaining standard errors and confidence intervals of composite reliability coefficients based on bootstrap methods and using a structural-equation-modeling framework for estimating the composite reliability of congeneric measures (T. Raykov, 1997). Demonstrates the approach with simulated data. (SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Reliability, Simulation

Crawford, J. R.; Deary, Ian J.; Allan, Katherine M.; Gustafsson, Jan-Eric – Intelligence, 1998
Confirmatory factor analysis was used to test models of the relationship between inspection time (IT) and psychometric measures of intelligence in a sample of 134 healthy adults in the United Kingdom. A nested structural equation modeling approach shows that IT is most strongly associated with the Perceptual-Organizational factor of the Wechsler…
Descriptors: Adults, Foreign Countries, Inspection, Intelligence

Hox, Joop J.; Maas, Cora J. M. – Structural Equation Modeling, 2001
Assessed the robustness of an estimation method for multilevel and path analysis with hierarchical data proposed by B. Muthen (1989) with unequal groups and small sample sizes and in the presence of a low or high intraclass correlation. Simulation results show the effects of varying these conditions on the within-group and between-groups part of…
Descriptors: Estimation (Mathematics), Robustness (Statistics), Sample Size, Simulation

Skrondal, Anders – Multivariate Behavioral Research, 2000
Discusses the design and analysis of Monte Carlo experiments, with special reference to structural equation modeling. Outlines three fundamental challenges of Monte Carlo approaches and suggests some alternative procedures that challenge conventional wisdom. Asserts that comprehensive Monte Carlo studies can be done with a personal computer if the…
Descriptors: Monte Carlo Methods, Research Design, Research Methodology, Structural Equation Models

Herting, Jerald R.; Costner, Herbert L. – Structural Equation Modeling, 2000
Examines some positions in various arguments related to the proper number of factors and proper number of steps when using structural equation models. Defines the issue in estimating structural equation models as a problem of specifying a model appropriately based on theoretical concerns and then diagnosing ills in the model as well as possible.…
Descriptors: Factor Analysis, Factor Structure, Research Methodology, Structural Equation Models

Hancock, Gregory R.; Freeman, Mara J. – Educational and Psychological Measurement, 2001
Provides select power and sample size tables and interpolation strategies associated with the root mean square error of approximation test of not close fit under standard assumed conditions. The goal is to inform researchers conducting structural equation modeling about power limitations when testing a model. (SLD)
Descriptors: Goodness of Fit, Power (Statistics), Sample Size, Structural Equation Models

Enders, Craig K.; Bandalos, Deborah L. – Structural Equation Modeling, 2001
Used Monte Carlo simulation to examine the performance of four missing data methods in structural equation models: (1)full information maximum likelihood (FIML); (2) listwise deletion; (3) pairwise deletion; and (4) similar response pattern imputation. Results show that FIML estimation is superior across all conditions of the design. (SLD)
Descriptors: Maximum Likelihood Statistics, Monte Carlo Methods, Simulation, Structural Equation Models
Sivo, Stephen; Fan, Xitao; Witta, Lea – Structural Equation Modeling: A Multidisciplinary Journal, 2005
The purpose of this study was to evaluate the robustness of estimated growth curve models when there is stationary autocorrelation among manifest variable errors. The results suggest that when, in practice, growth curve models are fitted to longitudinal data, alternative rival hypotheses to consider would include growth models that also specify…
Descriptors: Structural Equation Models, Interaction, Correlation, Test Bias

Vautier, Stephane; Mullet, Etienne; Jmel, Said – Social Indicators Research, 2004
Structural invariance of self-rated satisfaction with life data was assessed using four data sets collected in earlier studies by using the Satisfaction With Life Scale. Three measurement models were compared to account for structural variability of the data. Strict structural invariance was rejected. Departure from the one-factor model was only…
Descriptors: Measures (Individuals), Reliability, Life Satisfaction, Factor Structure

Epstein, Jennifer A.; Griffin, Kenneth W.; Botvin, Gilbert J. – Journal of Youth and Adolescence, 2004
Prior studies have found inconsistent relationships between measures of self-concept and adolescent alcohol use. The current study explored whether the link between various measures of self-concept and alcohol use depends on gender. In addition, earlier work suggested a focus on negative self-esteem (i.e., self-derogation) might be more useful in…
Descriptors: Junior High Schools, Negative Attitudes, Females, Drinking
Raykov, Tenko; du Toit, Stephen H. C. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
A method for estimation of reliability for multiple-component measuring instruments with clustered data is outlined. The approach is applicable with hierarchical designs where individuals are nested within higher order units and exhibit possibly related performance on components of a scale of interest. The procedure is developed within the…
Descriptors: Structural Equation Models, Computation, Measurement Techniques, Test Reliability
Curran, Patrick J. – Multivariate Behavioral Research, 2003
A core assumption of the standard multiple regression model is independence of residuals, the violation of which results in biased standard errors and test statistics. The structural equation model (SEM) generalizes the regression model in several key ways, but the SEM also assumes independence of residuals. The multilevel model (MLM) was…
Descriptors: Structural Equation Models, Multiple Regression Analysis, Observation, Mathematical Models
Hershberger, Scott L. – Structural Equation Modeling: A Multidisciplinary Journal, 2003
This study examines the growth and development of structural equation modeling (SEM) from the years 1994 to 2001. The synchronous development and growth of the Structural Equation Modeling journal was also examined. Abstracts located on PsycINFO were used as the primary source of data. The major results of this investigation were clear: (a) The…
Descriptors: Primary Sources, Journal Articles, Structural Equation Models, Periodicals
Fan, Xitao; Fan, Xiaotao – Journal of Experimental Education, 2005
The authors investigated 2 issues concerning the power of latent growth modeling (LGM) in detecting linear growth: the effect of the number of repeated measurements on LGM's power in detecting linear growth and the comparison between LGM and some other approaches in terms of power for detecting linear growth. A Monte Carlo simulation design was…
Descriptors: Statistical Analysis, Sample Size, Monte Carlo Methods, Structural Equation Models

Trusty, Jerry; Ng, Kok-Mun; Watts, Richard E. – Journal of Counseling and Development, 2005
The effects of adult attachment on emotional empathy were investigated using a sample of master's-degree level counseling students. Through structural equation modeling, the authors found that the latent attachment dimensions of avoidance and anxiety work in tandem in their effects on empathy. Lower avoidance and higher anxiety were associated…
Descriptors: Structural Equation Models, Empathy, Counselor Educators, Counseling