Department of Statistics, UCLA

The vast majority of structural equation models contain no mean structure, that is, the population means are estimated at the sample means and are then eliminated from modeling consideration. Generalized least squares methods are proposed to estimate potential mean structure parameters and to evaluate whether the given model can be successfully augmented with a mean structure. A simulation evaluates the performance of some alternative tests. A method that takes variability due to estimation of covariance structure parameters into account in the mean structure estimator, as well as in the weight matrix of the generalized least squares function, performs best. In small samples, the F-test and Yuan-Bentler adjusted X2 test perform best.