A Monte Carlo study evaluated the effectiveness of different factor analysis extraction and rotation methods for identifying the known population multiple-indicator measurement model. Results demonstrate that exploratory factor analysis can contribute to a useful heuristic strategy for model specification prior to cross-validation with…

Proposes a modified version of commonly employed item response models in a fully Bayesian framework and obtains inferences under the model using Markov chain Monte Carlo techniques. Demonstrates use of the model in a series of simulations and with operational data from the North Carolina Test of Computer Skills and the Test of Spoken English…

The sampling variability and zeta-values of parameter estimates for misspecified structural equation models were examined. A Monte Carlo study was used. Results are discussed in terms of asymptotic theory and the implications for the practice of structural equation models. (SLD)

The partitioning of squared Euclidean--E(sup 2)--distance between two vectors in M-dimensional space into the sum of squared lengths of vectors in mutually orthogonal subspaces is discussed. Applications to specific cluster analysis problems are provided (i.e., to design Monte Carlo studies for performance comparisons of several clustering methods…

A complete enumeration method and a Monte Carlo method are presented to calculate the probability distribution of arbitrary statistics of adjacency matrices when these matrices have the uniform distribution conditional on given row and column sums, and possibly on a given set of structural zeros. (SLD)

A method is proposed for investigating the intersection of item response functions in the nonparametric item-response-theory model of R. J. Mokken (1971). Results from a Monte Carlo study support the proposed use of the transposed data matrix H(sup T) as an extension to Mokken's approach. (SLD)

Whether it is possible to develop a classification function that identifies the underlying range restriction from sample information alone was investigated in a simulation. Results indicate that such a function is possible. The procedure was found to be relatively accurate, robust, and powerful. (SLD)

This article shows how a multivariate approximate degrees of freedom procedure based on the Welch-James procedure as simplified by S. Johansen (1980) can be applied to the analysis of repeated measures designs without assuming covariance homogeneity. A Monte Carlo study illustrates the approach. (SLD)

The challenge of multiple comparisons is to maximize the power for answering specific research questions, while still maintaining control over the rate of Type I error. Several multiple comparison procedures have been suggested to meet this challenge. The stagewise protected procedure (SPP) of A. J. Klockars and G. R. Hancock tests null hypotheses…

Using computer simulation data, the effect of a single global outlier in two-group classification analysis was explored in terms of the outcome variables of change in classification results (PCHNG), change in misclassification rate (MISDIF), and change in precision of misclassification rate estimation. The precision of misclassification rate…

Three techniques for estimating Kuder Richardson reliability (KR20) coefficients for incomplete data are contrasted. The methods are: (1) Henderson's Method 1 (analysis of variance, or ANOVA); (2) Henderson's Method 3 (FITCO); and (3) Koch's method of symmetric sums (SYSUM). A Monte Carlo simulation was used to assess the precision of the three…

This paper describes a simulation that determines the adequacy of various indices as decision criteria for assessing unidimensionality. Using the sum of absolute residuals from the two-parameter latent trait model, indices were obtained that could discriminate between one latent trait and more than one latent trait. (Author/BW)

This paper aims to describe a Bayesian approach to modeling and estimating cognitive models both in terms of statistical machinery and actual instrument development. Such a method taps the knowledge of experts to provide initial estimates for the probabilistic relationships among the variables in a multivariate latent variable model and refines…

Monte Carlo techniques were used to examine regression approaches to external unfolding. The present analysis examined the technique to determine if various characteristics of the points are recovered (such as ideal points). Generally, monotonic analyses resulted in good recovery. (TJH)

Using a Monte Carlo simulation, a bootstrap procedure was evaluated for setting a confidence interval on the unrestricted population correlation (rho) assuming various degrees of incomplete truncation on the predictor. Sample size was the most important factor in determining accuracy and stability. Sample size should be at least 50. (SLD)