Testing nonnested structural equation models.

Testing Multinormality in Two-level Structural Equation Models

Bayesian Estimation and Testing of Structural Equation Models

The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformat...

Testing Complex Correlational Hypotheses With Structural Equation Models

It is often of interest to estimate partial or semipartial correlation coefficients as indexes of the linear association between 2 variables after partialing one or both for the influence of covariates. Squaring these coefficients expresses the proportion of variance in 1 variable explained by the other variable after controlling for covariates. Methods exist for testing hypotheses about the eq...

Testing structural equation models: The effect of kurtosis

Various chi-square statistics are used for testing structural equation models. A commonly used chi-square is the Satorra-Bentler (SB) statistic. This is a normal-theory chi-square corrected for non-normality in the observed variables. The relationship between the SB statistic and kurtosis is developed and it is shown that the SB statistic tends to decrease with increasing kurtosis if the model ...

Testing Structural Equation Models or Detection of Misspecifications?