Structural equation models offer a valuable tool for delineating the complicated interrelationships among multiple variables, including observed and latent variables. Over the last few decades, structural equation models have successfully analyzed complete and right-censored survival data, exemplified by wide applications in psychological, social,…

A general class of nonhierarchical clustering models and associated algorithms for fitting them are presented. These models generalize the Shepard-Arabie Additive clusters model. Two applications are given and extensions to three-way models, nonmetric analyses, and other model specifications are provided. (Author/JKS)

Rubin and Thayer recently presented equations to implement maximum likelihood estimation in factor analysis via the EM algorithm. It is argued here that the advantages of using the EM algorithm remain to be demonstrated. (Author/JKS)

The authors respond to a criticism of their earlier article concerning the use of the EM algorithm in maximum likelihood factor analysis. Also included are the comments made by the reviewers of this article. (JKS)

Highlights semantic links and shows how the semantic content of hypertext links can be used for information retrieval. Discussion includes indexing and retrieval algorithms that exploit link content and node content; retrieval strategies exploiting semantic links, including conventional retrieval and constrained spreading activation techniques;…

An empirical method (PRESS) for examining and contrasting the cross-validated prediction accuracies of some popular algorithms for weighting predictor variables was advanced and examined. The sample specific PRESS method was suggested as most appropriate when selecting among several alternative weighting algorithms to achieve maximum…

Item response curves for a set of binary responses are studied from a Bayesian viewpoint of estimating the item parameters. For the two-parameter logistic model with normally distributed ability, restricted bivariate beta priors are used to illustrate the computation of the posterior mode via the EM algorithm. (Author/LMO)

The effectiveness of Stout's procedure for assessing latent trait unidimensionality was studied. Strong empirical evidence of the utility of the statistical test in a variety of settings is provided. The procedure was modified to correct for increased bias, and a new algorithm to determine the size of assessment sub-tests was used. The following…

Maximum likelihood procedures are presented for a general model to unify the various models and techniques that have been proposed for item analysis. Unconditional maximum likelihood estimation, proposed by Wright and Haberman, and conditional maximum likelihood estimation, proposed by Rasch and Andersen, are shown as important special cases. (JAZ)

This article describes a Bayesian framework for estimation in item response models, with two-stage distributions on both item and examinee populations. Strategies for point and interval estimation are discussed, and a general procedure based on the EM algorithm is presented. (Author/LMO)

An extension to the partial credit model, the linear partial credit model, is considered under the assumption of a certain linear decomposition of the item x category parameters into basic parameters. A conditional maximum likelihood algorithm for estimating basic parameters is presented and illustrated with simulation and an empirical study. (SLD)

The suggestion that the IDIOSCAL model be fitted by the TUCKALS2 algorithm for three-way components analysis is examined. The claim that resulting coordinate matrices will be identical is supported when the data matrices are semidefinite. Counterexamples for indefinite matrices are also constructed. (SLD)

A statistical power algorithm based on the Fisher Z method is developed for cutoff-based random clinical trials and the single cutoff-point (regression-discontinuity) design that has no randomization. This article quantifies power and sample size estimates for various levels of power and cutoff-based assignment. (Author/SLD)

An empirical method called Predicted Error Sum of Squares (PRESS) is advanced and studied. This method is used to examine the cross-validated prediction accuracies of some popular algorithms for weighted predictor variables. The weighting methods that were considered were ordinary least squares, ridge regression, regression on principal…

The dynamic linear model or Kalman filtering model provides a useful methodology for predicting the past, present, and future states of a dynamic system, such as an object in motion or an economic or social indicator that is changing systematically with time. Recursive likelihood methods for adaptive Kalman filtering and smoothing are developed.…