The Vale and Maurelli algorithm is a widely used method that allows researchers to generate multivariate, nonnormal data with user-specified levels of skewness, excess kurtosis, and a correlation structure. Before obtaining the desired correlation structure, a transitional step requires the user to calculate the roots of a cubic polynomial…

This computer simulation study evaluates the robustness of the nonparametric Levene test of equal variances (Nordstokke & Zumbo, 2010) when sampling from populations with unequal (and unknown) means. Testing for population mean differences when population variances are unknown and possibly unequal is often referred to as the Behrens-Fisher…

To further understand the properties of data-generation algorithms for multivariate, nonnormal data, two Monte Carlo simulation studies comparing the Vale and Maurelli method and the Headrick fifth-order polynomial method were implemented. Combinations of skewness and kurtosis found in four published articles were run and attention was…

Previous studies have rarely examined the impact of outliers on the decisions about the number of factors to extract in an exploratory factor analysis. The few studies that have investigated this issue have arrived at contradictory conclusions regarding whether outliers inflated or deflated the number of factors extracted. By systematically…

In a recent Monte Carlo simulation study, Liu and Zumbo showed that outliers can severely inflate the estimates of Cronbach's coefficient alpha for continuous item response data--visual analogue response format. Little, however, is known about the effect of outliers for ordinal item response data--also commonly referred to as Likert, Likert-type,…

It is argued that instead of using the standardized discriminant coefficients to assess variable importance, the parallel and total discriminant ratio coefficients (DRCs) proposed by D. R. Thomas (1992) should be used, and parallel DRCs should be adopted as the actual importance measures. (SLD)

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…

Many measures found in educational research are ordered categorical response variables that are empirical realizations of an underlying normally distributed variate. These ordered categorical variables are commonly referred to as Likert or rating scale data. Regression models are commonly fit using these ordered categorical variables as the…

This article reviews the problems associated with using item response theory (IRT)-based latent variable scores for analytical modeling, discusses the connection between IRT and structural equation modeling (SEM)-based latent regression modeling for discrete data, and compares regression parameter estimates obtained using predicted IRT scores and…