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)

MAXCOV-HITMAX was invented by Paul Meehl as a tool for the detection of latent taxonic structures (i.e., structures in which the latent variable, u, is not continuously, but rather Bernoulli, distributed). It involves the examination of the shape of a certain conditional covariance function and is based on Meehl's claims that (R1) Taxonic…

Three estimates of the probabilities of correct classification in predictive discriminant analysis were computed using mathematical formulas, resubstitution, and external analyses: (1) optimal hit rate; (2) actual hit rate; and (3) expected actual hit rate. Methods were compared using Monte Carlo sampling from two data sets. (Author/GDC)

The ability of the NORMIX algorithm to recover overlapping population structures was compared to the OVERCLUS procedure and another clustering procedure in a Monte Carlo study. NORMIX is found to be more accurate than other procedures in recovering overlapping population structure when appropriate implementation options are specified. (SLD)

Studied the small sample behavior of several test statistics based on the maximum-likelihood estimator but designed to perform better with nonnormal data. Monte Carlo results indicate the satisfactory performance of the "F" statistic recently proposed by K. Yuan and P. Bentler (1997). (SLD)

A Monte Carlo study was made of the recovery of cluster structure in binary data by five hierarchical techniques, with a view to finding which data structure factors influenced recovery and to determining differences between clustering methods with respect to these factors. (LMO)

Tau, Lambda, and Kappa are measures developed for the analysis of discrete multivariate data of the type represented by stimulus response confusion matrices. The accuracy with which they may be estimated from small sample confusion matrices is investigated by Monte Carlo methods. (Author/LMO)

The empirical performance under null/alternative hypotheses of the likelihood ratio difference test (LRDT); Lagrange Multiplier test (evaluating the impact of model modification with a specific model); and Wald test (using a general model) were compared. The new tests for covariance structure analysis performed as well as did the LRDT. (RLC)

A maximum likelihood approach to correlational outlier identification is introduced and compared to the Mahalanobis D squared and Comrey D statistics through Monte Carlo simulation. Identification performance depends on the nature of correlational outliers and the measure used, but the maximum likelihood approach is the most robust performance…

Multivariate permutation tests are described, and some are suggested as substitutions for Hotelling's one-sample T2 test in common situations in behavioral science research. A Monte Carlo study shows advantages of these tests when the T2 test fails or is suspect. (SLD)

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)

The standard univariate and multivariate methods are conventionally used to analyze continuous data from groups by trials repeated measures designs, in spite of being extremely sensitive to departures from the multisample sphericity assumption when group sizes are unequal. However, in the last 10 years several authors have offered alternative…

Factor analysis, image analysis, and principal component analysis are compared with respect to the factor patterns they would produce under various conditions. The general conclusion that is reached is that the three methods produce results that are equivalent. (Author/JKS)

A Monte Carlo study was conducted to assess the robustness of the limited information two-stage least squares (2SLS) estimation procedure on a confirmatory factor analysis model with nonnormal distributions. Full information maximum likelihood methods were used for comparison. One hundred model replications were used to generate data. (TJH)