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Yuan, Ke-Hai; Bentler, Peter M. – Psychometrika, 2004
Since data in social and behavioral sciences are often hierarchically organized, special statistical procedures for covariance structure models have been developed to reflect such hierarchical structures. Most of these developments are based on a multivariate normality distribution assumption, which may not be realistic for practical data. It is…
Descriptors: Statistical Analysis, Statistical Inference, Statistical Distributions, Multivariate Analysis

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
Yuan, Ke-Hai; Bentler, Peter M.; Chan, Wai – Psychometrika, 2004
Data in social and behavioral sciences typically possess heavy tails. Structural equation modeling is commonly used in analyzing interrelations among variables of such data. Classical methods for structural equation modeling fit a proposed model to the sample covariance matrix, which can lead to very inefficient parameter estimates. By fitting a…
Descriptors: Structural Equation Models, Statistical Distributions, Evaluation Methods, Data Analysis
Lee, Sik-Yum; Xia, Ye-Mao – Psychometrika, 2006
By means of more than a dozen user friendly packages, structural equation models (SEMs) are widely used in behavioral, education, social, and psychological research. As the underlying theory and methods in these packages are vulnerable to outliers and distributions with longer-than-normal tails, a fundamental problem in the field is the…
Descriptors: Maximum Likelihood Statistics, Statistical Distributions, Structural Equation Models, Robustness (Statistics)