Conducted a Monte Carlo study to compare various approaches to detecting differential item functioning (DIF) under a conceptualization of DIF that recognizes that observed data are a mixture of data from multiple latent populations or classes. Demonstrated the usefulness of the approach. (SLD)

Studied four different approaches for handling missing data for their capacity to mitigate against the effect of omitted responses on person location estimation. Results from a Monte Carlo study show that the hot-decking procedure performed best of the methods examined. (SLD)

Examines the ways in which level-1 outliers can impact the estimation of fixed effects and random effects in hierarchical models (HMs). Also outlines and illustrates the use of Markov Chain Monte Carlo algorithms for conducting sensitivity analyses under "t" level-1 assumptions, including algorithms for settings in which the degrees of…

Tested empirically the applicability of a method developed by S. Mattson for generating data on latent variables with controlled skewness and kurtosis of the observed variables. Monte Carlo simulation results suggest that Mattson's method appears to be a good approach to generate data with defined levels of skewness and kurtosis. (SLD)

This article examines using moment-based statistics to screen variables that are then used in clustering. A Monte Carlo study found that screening variables was a viable alternative to both ultrametric weighting and forward selection of variables. Advantages and disadvantages of screening are discussed. (SLD)

Investigated the effects of types and prevalence of response patterns that might be provided by nonattending respondents on Cronbach's alpha (L. Cronbach, 1970) using three simulated data sets. Effects were greater as a function of increased prevalence in the respondent group, but as few as 5% of some types of nonattending patterns had inflating…

Examined the optimal value of "k" for promax factor rotations through a Monte Carlo study involving 10,080 factor analyses. Results show that in factor-analytic studies using promax, the value of "k" may be set appropriately at 2, 3, or 4. (Author/SLD)

Examined the performance of DIMTEST, through simulation, for unidimensional and two-dimensional data that exhibited ceiling effects generated through changes in location and scale of the theta distribution. Results indicate that the power of DIMTEST is reduced as the location shifts upward and the scale shifts downward. Considers the selection…

A multidimensional scaling procedure is introduced that attempts to derive a spatial representation of stimuli unconfounded by the effect of subjects' degrees of familiarity with these stimuli. A Monte Carlo study investigating the extent to which the procedure recovers known parameters shows that the procedure succeeds in adjusting for…

Illustrates the design and planning of Monte Carlo simulations, presenting nine steps in planning and performing a Monte Carlo analysis from developing a theoretically derived question of interest through summarizing the results. Uses a Monte Carlo simulation to illustrate many of the relevant points. (SLD)

Assessed two models for confirmatory factor analysis of multitrait-multimethod data through Monte Carlo simulation. The correlated traits-correlated methods (CTCM) and the correlated traits-correlated uniqueness (CTCU) models were compared. Results suggest that CTCU is a good alternative to CTCM in the typical multitrait-multimethod matrix, but…

The use of Monte Carlo methods demonstrated that a formula presented by M. G. Kendall for estimating Pearson's rho from tau is somewhat more accurate than a formula presented by K. Pearson for estimating Pearson's rho from a Spearman's rho coefficient. Implications for meta-analysis of correlations are discussed. (SLD)

Used Monte Carlo methods to evaluate the adequacy of cluster analysis to recover group membership based on simulated latent growth curve (LCG) models. Cluster analysis failed to recover growth subtypes adequately when the difference between growth curves was shape only. Discusses circumstances under which it was more successful. (SLD)

Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)

Evidence-based practice approaches to interventions has come of age and promises to provide a new standard of excellence for school psychologists. This article describes several definitions of evidence-based practice and the problems associated with traditional statistical analyses that rely on rejection of the null hypothesis for the…