The effect of scale selection on error in calibrating item and ability parameters was investigated, with particular reference to the standardized mean-squared difference (SMSD) statistic. Through simulation, three scaling methods for selecting the common scale were used to demonstrate their effects on SMSD values. (SLD)

Type I error rates and rejection rates for three-dimensionality assessment procedures were studied with data sets simulated to reflect short tests and small samples. Results show that the G-squared difference test (D. Bock, R. Gibbons, and E. Muraki, 1988) suffered from a severely inflated Type I error rate at all conditions simulated. (SLD)

The normality of number distributions generated by various random-number generators were studied, focusing on when the random-number generator reached a normal distribution and at what sample size. Findings suggest the steps that should be followed when using a random-number generator in a Monte Carlo simulation. (SLD)

The problem of chance model modifications under varying levels of sample size, model size, and severity of misspecification in confirmatory factor analysis models was examined through Monte Carlo simulations. Findings suggest that practitioners should exercise caution when interpreting modified models unless sample size is quite large. (SLD)

Discusses decision making and suggests that using simulation techniques based on a sophisticated decision support system facilitates the identification of utility-maximizing strategies. The negotiation training model is described, and preliminary results based on simulation runs are reported. (LRW)

Proposes a new regression correction for the SIBTEST statistical tests (R. Shealy and W. Stout, 1993) that essentially uses a two-segment piecewise linear regression of the true on observed matching subtest scores. A simulation study illustrates the approach. (SLD)

Presents a game called the Meiosis Shuffle that helps students simulate the process of meiosis in which homologous cards representing chromosomes pair up, line up, and split apart. Students respond well to the simulation and are better able to conceptualize what chromosomes do and how independent assortment causes genetic variation. (CCM)

Compares eight models for analyzing count data through simulation in the context of prediction of absenteeism to indicate the extent to which each model produces false positives. Results suggest that ordinary least-squares regression does not produce more false positives than expected by chance. The Tobit and Poisson models do yield too many false…

Used simulated data to test the integrity of orthogonal factor solutions when varying sample size, factor pattern/structure coefficient magnitude, method of extraction, number of variables, number of factors, and degree of overextraction. Discusses implications of results with regard to overextraction. (SLD)

Develops an item-parameter estimation procedure using an EM algorithm for the continuous-response model (F. Samejima, 1973). Examines the usefulness of this model using simulated data. Results show that the procedure performs well in estimating items and theta parameters. (SLD)

Describes a co-evolutionary model for supporting the emergence of authenticity through a partnership between preservice teachers and practicing teachers who collaborated in real-world tasks. Discusses authenticity and participatory learning; simulation models; participation models; uses of technology; communities of practice; power and control;…

Developed a simulation model to predict the effects of policies for reducing adolescent smoking initiation. The model projected numbers of smokers, never smokers, and ex-smokers by age, sex, and race/ethnicity and effects of reductions in youth initiation. Results predicted that even if tobacco policies eliminated youth initiation, the number of…

Describes the implementation of a standard Pearson chi-square statistic to test the null hypothesis of bivariate normality for latent variables in the Type I censored model. Assesses the behavior of the statistic through simulation and illustrates the statistic through an empirical example. Discusses limitations of the test. (Author/SLD)

Simulated data for factor analytic models is used in the evaluation of three methods for controlling Type I errors: (1) the standard approach that involves testing each parameter at the 0.05 level; (2) the Bonferroni approach; and (3) a simultaneous test procedure (STP). Advantages offered by the Bonferroni approach are discussed. (SLD)

Presents a four-part theoretical treatment of the planning of speech movements that favors models in which the only invariant targets are regions in auditory perceptual space over models that posit invariant construction targets. Computer simulations illustrate the models. (SLD)