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Ravand, Hamdollah; Baghaei, Purya – Practical Assessment, Research & Evaluation, 2016
Structural equation modeling (SEM) has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and…
Descriptors: Least Squares Statistics, Structural Equation Models, Nonparametric Statistics, Sample Size
Finch, Holmes – Applied Psychological Measurement, 2010
The accuracy of item parameter estimates in the multidimensional item response theory (MIRT) model context is one that has not been researched in great detail. This study examines the ability of two confirmatory factor analysis models specifically for dichotomous data to properly estimate item parameters using common formulae for converting factor…
Descriptors: Item Response Theory, Computation, Factor Analysis, Models

Raykov, Tenko; Little, Todd D. – Educational and Psychological Measurement, 1999
Describes a method for evaluating results of Procrustean rotation to a target factor pattern matrix in exploratory factor analysis. The approach, based on the bootstrap method, yields empirical approximations of the sampling distributions of: (1) differences between target elements and rotated factor pattern matrices; and (2) the overall…
Descriptors: Computer Software, Evaluation Methods, Factor Analysis, Goodness of Fit

Bollen, Kenneth A. – Psychometrika, 1996
An alternative two-stage least squares (2SLS) estimator of the parameters in LISREL type models is proposed and contrasted with existing estimators. The new 2SLS estimator allows observed and latent variables to originate from nonnormal distributions, is consistent, has a known asymptotic covariance matrix, and can be estimated with standard…
Descriptors: Computer Software, Equations (Mathematics), Estimation (Mathematics), Factor Analysis

Ethington, Corinna A. – Journal of Experimental Education, 1987
This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical variables. The analysis of mixed matrices produced estimates that closely approximated the model parameters except where dichotomous variables were…
Descriptors: Computer Software, Estimation (Mathematics), Factor Analysis, Least Squares Statistics