Topic models are mathematical and statistical models used to analyze textual data. The objective of topic models is to gain information about the latent semantic space of a set of related textual data. The semantic space of a set of textual data contains the relationship between documents and words and how they are used. Topic models are becoming…

Improvements of the Gaussian quadrature in conjunction with the Newton-Raphson iteration technique (TM 000 789) are discussed as effective methods of calculating the bivariate normal correlation coefficient. (CK)

Evaluated the performance of several alternative cluster analytic approaches to initial model specification using population parameter analyses and a Monte Carlo simulation. Of the six cluster approaches evaluated, the one using the correlations of item correlations as a proximity metric and average linking as a clustering algorithm performed the…

An algorithm for obtaining initial values for the minimization process in covariance structure analysis is developed that is more generally applicable for computing parameters connected to latent variables than the currently existing ones. The algorithm is formulated in terms of the RAM model but can be extended. (SLD)

A new basic algorithm is discussed that may be used to do factor analysis by any of these three methods: (1) unweighted least squares, (2) generalized least squares, or (3) maximum likelihood. (CK)

Factorial modeling is justified as a method for analyzing correlations in support of causal inference. The method is illustrated and compared to path analysis, LISREL-type analysis, canonical correlation, and commonality analysis. Predictions of impacts of policy manipulations are demonstrated. (Author/CP)

A mathematical formula is introduced for the effect of integrating data. A method is then derived to eliminate the effect from correlations of variables, including mean composites, thus allowing for a clustering algorithm that requires allocation of variables according to the magnitude of their correlations. Examples illustrate the procedure. (SLD)

Proposes a quadratic programming, least squares solution to Carroll's weighted unfolding model with nonnegativity constraints imposed on weights. It can be used to test various hypotheses about the weighted unfolding model with or without constraints. (RC)

The contention is made that group performance data are useful in the construction and interpretation of criterion-referenced tests. The Mastery Learning Test Model, which was developed for analyzing criterion-referenced test data, is described. An estimate of the proportion of students in an instructional group having achieved the referent…

This paper discusses the use of latent class structure as a modelling framework for tests in which much of the data conforms to a relatively small number of systematic patterns. Application of this framework to the analysis of tests has been limited because available parameter estimation algorithms can only handle a relatively small number of…