A structural equation model is proposed with a generalized measurement part, allowing for dichotomous and ordered categorical variables (indicators) in addition to continuous ones. A computationally feasible three-stage estimator is proposed for any combination of observed variable types. Two multiple-indicator modeling examples are given.…

Structural equation models require formidable computational techniques. Testing the goodness of fit involves discrepancies between original correlations among variables and correlations estimated by solved path coefficients. A BASIC computer program which solves these problems is presented and discussed. (Author/GDC)

The dangers of overlooking time-honored cautions in the making causal interpretations of data analyses from correlational studies when using highly sophisticated computer programs and their associated techniques are discussed. (JKS)

Since computer programs have been available for estimating and testing linear causal models, these models have been used increasingly in the behavioral sciences. This paper discusses the problem that very different causal structures may fit the same set of data equally well. (Author/LMO)

The Werts-Linn procedure for dealing with categorical errors of measurement in "Comments on Boyle's 'Path Analysis and Ordinal Data'" in The American Journal of Sociology, volume 76, number 6, May 1971, is shown to be inappropriate to the problem of ordered categories. (For related document, see TM 002 301.) (DB)

Covariance structures associated with linear structural equation models are discussed. Algorithms for computing maximum likelihood estimates (namely, the EM algorithm) are reviewed. An example of using likelihood ratio tests based on complete and incomplete data to improve the fit of a model is given. (SLD)

This Monte Carlo study examined the validity of the chi-square test for model evaluation in different instances of misspecification and sample size. The usefulness of the chi-square difference statistic to compare competing structures and improvement in fit is also addressed. (Author/BS)

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 manifest variables. Two types of correlation matrices were analyzed; one containing Pearson product-moment correlations and one containing tetrachoric,…

A general method for estimating the unknown coefficients in a set of linear structural equations is described. In its most general form the method allows for both errors in equations (residuals, disturbances) and errors in variables (errors of measurement, observational errors) and yields estimates of the residual variance-covariance matrix and…