Attempts are made to improve the previously used procedure for multidimensional scaling in the measure of conceptual level. Monte Carlo simulation runs and a laboratory experiment highlight potential incongruities related to the degree of error in the input data required by that process. Methodological recommendations are briefly evaluated.…

A program designed to calculate pi using a Monte Carlo simulation based on "throwing darts" at a quarter circle of unit radius inscribed in a unit square is presented. (MP)

Type I error rates for the likelihood ratio test for detecting differential item functioning (DIF) were investigated using Monte Carlo simulations. Type I error rates for the two-parameter model were within theoretically expected values at each alpha level, but those for the three-parameter model were not. (SLD)

Developed an item response model for characterizing test-compromise that enables the estimation of item preview and score-gain distributions. In the approach, models parameters and posterior distributions are estimated by Markov Chain Monte Carlo procedures. Simulation study results suggest that when at least some test items are known to be…

The Dutch Identity is presented as a useful tool for expressing the basic equations of item response models that relate the manifest probabilities to the item response functions and the latent trait distribution. Ways in which the identity may be exploited are suggested and illustrated. (SLD)

Statistical properties of person fit indices are reviewed as indicators of the extent to which a person's score pattern is in agreement with a measurement model. Distribution of a fit index and ability-free fit evaluation are discussed. The null distribution was simulated for a test of 20 items. (SLD)

A method for estimating the first eigenvalue of random data correlation matrices is reported, and its precision is demonstrated via comparison to the method of S. J. Allen and R. Hubbard (1986). Data generated in Monte Carlo simulations with 10 sample sizes reaching up to 1,000 were used. (SLD)

Two new methods of estimating the mean population correlation (M) and the standard deviation of population correlations (SD) were suggested and tested by Monte Carlo simulations. Results show no consistent advantage to using the Pearson correlation or Fisher's Z in estimating M or SD; estimates from all methods are similar. (SLD)

This paper explains how to obtain generally robust and powerful analyses with any of the recommended nonorthogonal solutions by adapting a modification of the Welch-James procedure for comparing means when population variances are heterogeneous. Results from a Monte Carlo study support use of the procedure. (SLD)

TSCALE, a multidimensional scaling procedure based on the contrast model of A. Tversky for asymmetric three-way, two-mode proximity data, is presented. TSCALE conceptualizes a latent dimensional structure to describe the judgmental stimuli. A Monte Carlo analysis and two consumer psychology applications illustrate the procedure. (SLD)

Six stepwise multiple-comparison procedures for repeated-measures means were compared for their overall familywise rates of Type I error when multisample sphericity and multivariate normality were not satisfied. Robust stepwise procedures were identified by Keselman, Keselman, and Shaffer (1991) with respect to three definitions of power. (SLD)

Monte Carlo methods were used to evaluate the degree to which canonical function and structure coefficients may be differentially sensitive to sampling error. For each of 64 research situations, 1,000 random samples were drawn. Both sets of coefficients were roughly equally influenced; some exceptions are noted. (SLD)

Based on the usual factor analysis model, this paper investigates the relationship between improper solutions and the number of factors. The properties of the noniterative estimation method of M. Ihara and Y. Kano in exploratory factor analysis are also discussed. The estimators were compared in a Monte Carlo experiment. (TJH)

Using Monte Carlo methods, the applicability of large sample theory to maximum likelihood estimates of total indirect effects in sample sizes of 50, 100, 200, 400, and 800 was studied. Samples of at least 200 and 400 are required for the recursive and nonrecursive models, respectively, that were assessed. (TJH)

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)