This paper discusses a new form of specifying and normalizing a Linear Logistic Test Model (LLTM) as suggested by Bechger, Verstralen, and Verhelst ("Psychometrika," 2002). It is shown that there are infinitely many ways to specify the same normalization. Moreover, the relationship between some of their results and equivalent previous…

Using LISREL, the only types of constraints allowed are fixing parameters at a constant value and constraining parameters to be equal. In this paper, two new concepts ("phantom" and "imaginary" latent variables) are introduced which allow fairly general equality and inequality constraints on factor loadings and structural model…

A general latent variable model allows for maximum likelihood estimation with missing data. LISREL and LISCOMP programs may be used to carry out this estimation. Simulated data were generated. The proposed Full, Quasi-Likelihood estimator was found to be superior to listwise present quasi-likelihood and pairwise present approaches. (Author/GDC)

Two discrimination coefficients, known as "disco" and "odisco," are proposed for measuring the extent of overlap in distributions as a direct function of the variance between the arithmetic means. These coefficients are related to K. Pearson's "eta" (1905) and R. A. Fisher's "F" (1950). (SLD)

A variety of paired comparison, triple comparison, and ranking experiments are discussed as generalized linear models. All such models can be easily fit by maximum likelihood using the GLIM computer package. Examples are presented for a variety of cases using GLIM. (SLD)

An implementation of the Gauss-Newton algorithm for the analysis of covariance structure that is specifically adapted for high-level computer languages is reviewed. This simple method for estimating structural equation models is useful for a variety of standard models, as is illustrated. (SLD)