A Monte Carlo study compared the accuracy of different estimates of the standard error of correlations corrected for restriction in range. The procedure suggested by P. Bobko and A. Rieck (1980) generated the most accurate estimates of the standard error. Aspects of accuracy are discussed. (SLD)

Monte Carlo study results show that the runs test yields markedly asymmetrical error rates in the two tails and that neither directional nor nondirectional tests are satisfactory with respect to Type I errors. The test is not recommended for evaluating the independence of errors in time-series regression models. (SLD)

This Monte Carlo study examined the impact of misspecifying the [big sum] matrix in longitudinal data analysis under both the multilevel model and mixed model frameworks. Under the multilevel model approach, under-specification and general-misspecification of the [big sum] matrix usually resulted in overestimation of the variances of the random…

The purpose of this study was to examine the potential impact of selected methodological factors on the validity of conclusions from reliability generalization (RG) studies. The study focused on four factors; (1) missing data in the primary studies; (2) transformation of sample reliability estimates; (3) use of sample weights for estimating mean…

The standard error of an equipercentile equating is derived for four situations. Some numerical results are checked by Monte Carlo methods. Numerical standard errors are computed for two sets of real data. Standard errors of linear and equipercentile equating are compared. (Author)

A Monte Carlo study involving 1,000 random samples from each of 64 different population matrices investigated bias in both canonical correlation and redundancy coefficients. Results indicate that the Wherry correction provides a reasonable solution to this problem and that canonical results are not as biased as has been believed. (TJH)

The performance was studied of five small-sample statistics--by F. M. Lord, W. Kristof, Q. McNemar, R. A. Forsyth and L. S. Feldt, and J. P. Braden--that test whether two variables measure the same trait except for measurement error. Effects of non-normality were investigated. The McNemar statistic was most powerful. (TJH)

Effects of item parameters on ability estimation were investigated through Monte Carlo studies using the Expected-A-Posteriori estimation. Results show a significant effect of item discriminating parameter on standard error of ability estimation. As the discriminating parameter increases, the standard error decreases. (SLD)

Studied incorporating adjusted model fit information into the root mean square error of approximation fit index (RMSEA). Monte Carlo simulation results show that incorporating robust information into the RMSEA may yield improved performance for assessing model fit under nonnormal data situations. (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…

The impact of outliers on Cronbach's coefficient [alpha] has not been documented in the psychometric or statistical literature. This is an important gap because coefficient [alpha] is the most widely used measurement statistic in all of the social, educational, and health sciences. The impact of outliers on coefficient [alpha] is investigated for…

Tukey's Honestly Significant Difference (HSD) procedure (J. Tukey, 1953) is probably the most recommended and used procedure for controlling Type I error rate when making multiple pairwise comparisons as follow-ups to a significant omnibus F test. This study compared observed Type I errors with nominal alphas of 0.01, 0.05, and 0.10 compared for…

A procedure was developed to analyze data with missing observations by extracting data from a sparsely filled data matrix into analyzable smaller subsets of data. This subdividing method, based on the conceptual framework of meta-analysis, was accomplished by creating data sets that exhibit structural designs and then pooling variance components…

A nonmetric algorithm, pairwise partitioning, is developed to identify feature-based similarity structures. Presents theorems about the validity of the features identified by the algorithm, and reports results of Monte Carlo simulations that estimate the probabilities of identifying valid features for different feature structures and amounts of…

The sampling variability and zeta-values of parameter estimates for misspecified structural equation models were examined. A Monte Carlo study was used. Results are discussed in terms of asymptotic theory and the implications for the practice of structural equation models. (SLD)