A nonspatial operationalization of the Krumhansl distance-density model of similarity is presented. The conceptual model and empirical evidence are reviewed. A nonspatial, tree-fitting methodology is described, which is sufficiently flexible to fit several competing hypotheses of similarity formation. Extensions to spatial models, three-way…

A general approach for fitting a model to a data matrix by weighted least squares (WLS) is studied. The approach consists of iteratively performing steps of existing algorithms for ordinary least squares fitting of the same model and is based on maximizing a function that majorizes WLS loss function. (Author/SLD)

An alternating least squares algorithm is offered for fitting the DEcomposition into DIrectional COMponents (DEDICOM) model for representing asymmetric relations among a set of objects via a set of coordinates for the objects on a limited number of dimensions. An algorithm is presented for fitting the IDIOSCAL model in the least squares sense.…

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)

A model and a computer program for performing conjoint measurement is developed. (AG)

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)

Derivations of several item selection algorithms for use in fitting test items to target information functions (IFs) are described. These algorithms, which use an average growth approximation of target IFs, were tested by generating six test forms and were found to provide reliable fit. (SLD)

This study examined the application of the marginal maximum likelihood-EM algorithm to the parameter estimation problems of the normal ogive and logistic polytomous response models for Likert-type items. A rating scale model, based on F. Samejima's (1969) graded response model, was developed. (TJH)

This study examines the application of the marginal maximum likelihood (MML) EM algorithm to the parameter estimation problem of the three-parameter normal ogive and logistic polychotomous item response models. A three-parameter normal ogive model, the Graded Response model, has been developed on the basis of Samejima's two-parameter graded…

A method is proposed for constructing a population covariance matrix as the sum of a particular model plus a nonstochastic residual matrix, with the stipulation that the model holds with a prespecified lack of fit. The procedure is considered promising for Monte Carlo studies. (SLD)

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…

This paper reports on a project which has developed the general latent class model as a framework for representation of item responses. This framework can be used to represent data in applications such as mastery tests and other kinds of achievement tests, where there is reason to believe that current foundations are deficient. Methods of…