Using Monte Carlo methods, with item response data generated for a variety of test characteristics, procedures are developed for estimating item and ability parameters in homogeneous, unidimensional tests with person characteristic functions for different levels of the total raw score distribution. (SLD)

A method is presented that simultaneously estimates cluster membership and corresponding regression functions for a sample of observations or subjects. This methodology is presented with the simulated annealing-based algorithm. A set of Monte Carlo analyses is included to demonstrate the performance of the algorithm. (SLD)

A Monte Carlo study of the validity of the Inverse Scree Test under conditions where true group membership is known was conducted. Fifty cluster analyses of each distribution involving 2 to 5 true groups of 3,000 simulated subjects were made. Implications for the data analyst are discussed. (SLD)

Major issues related to index-of-fit conjoint analysis were addressed in this simulation study. Goals were to develop goodness-of-fit criteria for conjoint analysis; develop tests to determine the significance of conjoint analysis results; and calculate the power of the test of the null hypothesis of random data distribution. (SLD)

Procedures for implementing parallel analysis (PA) criteria in practice were compared, examining regression equation methods that can be used to estimate random data eigenvalues from known values of the sample size and number of variables. More internally accurate methods for determining PA criteria are presented. (SLD)

A Monte Carlo study determined the Inverse Scree Test's shape with various numbers of true groups and under different conditions of distribution shape and sample size. Six simulated distributions of 3,000 subjects each and 1 with 1,500 were created. Findings suggest relative distribution independence, number independence, and modest…

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)

In multivariate analysis of variance studies with small numbers of subjects (15 or less) per treatment level, probability values reported by the commercial statistical packages SAS and SPSS are conservative for F approximations based on Pillai's trace and liberal for F approximations based on the Hotelling-Lawley trace. Discusses results in terms…

Focusing on linear interpolation, an accurate method of implementing parallel analysis, this article contains tables of 95th percentile eigenvalues from random data than can be used with sample sizes of 50 to 500 subjects and between 5 and 50 variables. An empirical example illustrates how to obtain the eigenvalues. (SLD)

Signal detection experiments with 21 college students suggest that streakiness is a property of auditory and visual discrimination in that correct and incorrect responses have a positive sequential dependency. Monte-Carlo simulations of observed data sequences suggest that streaky performance results from wavelike variations in perceptual and…

A modification of Horn's parallel analysis is introduced that is based on the Monte Carlo simulation of the null distributions of the eigenvalues generated from a population correlation identity matrix. This modification reduces the tendency of the parallel analysis procedure to overextract or to extract poorly defined factors. (SLD)

A new parametric maximum likelihood procedure is proposed for estimating ultrametric trees for the analysis of conditional rank order proximity data. Technical aspects of the model and the estimation algorithm are discussed, and Monte Carlo results illustrate its application. A consumer psychology application is also examined. (SLD)

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)

This Monte Carlo simulation studied the relative power of 8 tests for sphericity in randomized block designs where sample size was small (10, 15, 20, and 30) and population covariance matrices of dimension-to-sample size ratio approached 1.0. The locally best invariant test demonstrated substantial power to detect departures from sphericity. (SLD)

A Monte Carlo simulation explored how to optimize power in the extreme groups strategy when sampling from nonnormal distributions. Results show that the optimum percent for the extreme group selection was approximately the same for all population shapes, except the extremely platykurtic (uniform) distribution. (SLD)