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Raykov, Tenko; Shrout, Patrick E. – Structural Equation Modeling, 2002
Discusses a method for obtaining point and interval estimates of reliability for composites of measures with a general structure. The approach is based on fitting a correspondingly constrained structural equation model and generalizes earlier covariance structure analysis methods for scale reliability estimation with congeneric tests. (SLD)
Descriptors: Estimation (Mathematics), Reliability, Structural Equation Models
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Li, Fuzhong; Duncan, Terry E.; Acock, Alan – Structural Equation Modeling, 2000
Presents an extension of the method of estimating interaction effects among latent variables to latent growth curve models developed by K. Joreskog and F. Yang (1996). Illustrates the procedure and discusses results in terms of practical and statistical problems associated with interaction analyses in latent curve models and structural equation…
Descriptors: Estimation (Mathematics), Interaction, Structural Equation Models
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Wall, Melanie M.; Amemiya, Yasuo – Journal of Educational and Behavioral Statistics, 2001
Considers the estimation of polynomial structural models and shows a limitation of an existing method. Introduces a new procedure, the generalized appended product indicator procedure, for nonlinear structural equation analysis. Addresses statistical issues associated with the procedure through simulation. (SLD)
Descriptors: Estimation (Mathematics), Simulation, Structural Equation Models
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Bentler, P. M.; Jamshidian, Mortaza – Applied Psychological Measurement, 1994
A general approach is proposed to avoid improper solutions in structural equation models. The constrained estimation approach presented, which is based on an adaptation of a globally convergent method for nonlinear programming, has worked well in all trials. (SLD)
Descriptors: Estimation (Mathematics), Statistical Analysis, Structural Equation Models
Berkovits, Ilona; Hancock, Gregory R. – 2000
A simulation study compared three methods of estimating parameters within structural equation models (SEM) with polytomous variables. These methods appear in three SEM computer software packages: (1) LISREL (Joreskog and Sorbom, 1996) with PRELIS (Joreskog and Sorbom); (2) EQS (Bentler, 1995); and (3) the new Mplus (Muthen and Muthen, 1998). The…
Descriptors: Computer Software, Estimation (Mathematics), Simulation, Structural Equation Models
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Coenders, Germa; Saris, Willem E.; Satorra, Albert – Structural Equation Modeling, 1997
A Monte Carlo study is reported that shows the comparative performance of alternative approaches under deviations from their respective assumptions in the case of structural equation models with latent variables with attention restricted to point estimates of model parameters. The conditional polychoric correlations method is shown most robust…
Descriptors: Estimation (Mathematics), Monte Carlo Methods, 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 – 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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Stapleton, Laura M. – Structural Equation Modeling, 2002
Studied the use of different weighting techniques in structural equation modeling and found, through simulation, that the use of an effective sample size weight provides unbiased estimates of key parameters and their sampling variances. Also discusses use of a popular normalization technique of scaling weights. (SLD)
Descriptors: Estimation (Mathematics), Sample Size, Scaling, Simulation
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Rigdon, Edward E. – Multivariate Behavioral Research, 1995
This article presents a straightforward classification system that is a necessary and sufficient condition for identification of the structural component of structural equation models of the block-recursive type with no more than two equations per block. Limitations of other identification techniques are discussed. (SLD)
Descriptors: Classification, Equations (Mathematics), Estimation (Mathematics), Identification
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Nevitt, Jonathan; Hancock, Gregory R. – Structural Equation Modeling, 2001
Evaluated the bootstrap method under varying conditions of nonnormality, sample size, model specification, and number of bootstrap samples drawn from the resampling space. Results for the bootstrap suggest the resampling-based method may be conservative in its control over model rejections, thus having an impact on the statistical power associated…
Descriptors: Estimation (Mathematics), Power (Statistics), Sample Size, Structural Equation Models
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
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Song, Xin-Yuan; Lee, Sik-Yum – Structural Equation Modeling, 2002
Developed a Bayesian approach for a general multigroup nonlinear factor analysis model that simultaneously obtains joint Bayesian estimates of the factor scores and the structural parameters subjected to some constraints across different groups. (SLD)
Descriptors: Bayesian Statistics, Estimation (Mathematics), Factor Analysis, Scores
Peer reviewed Peer reviewed
Joreskog, Karl G. – Psychometrika, 1994
Estimation of polychoric correlations is seen as a special case of the theory of parametric inference in contingency tables. the asymptotic covariance matrix of the estimated polychoric correlations is derived for the case when thresholds are estimated from univariate marginals and polychoric correlations are estimated from bivariate marginals for…
Descriptors: Equations (Mathematics), Estimation (Mathematics), Maximum Likelihood Statistics, Structural Equation Models
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Muthen, Bengt O.; Satorra, Albert – Psychometrika, 1995
B. O. Muthen (1984) formulated a general model and estimation procedure for structural equation modeling with a mixture of dichotomous, ordered categorical, and continuous measures of latent variables that was implemented in the LISCOMP program. This paper extends the description of the asymptotics and shows how the formulas can be derived.…
Descriptors: Estimation (Mathematics), Least Squares Statistics, Measurement Techniques, Structural Equation Models
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