The current study aims to evaluate the performance of three non-IRT procedures (i.e., normal approximation, Livingston-Lewis, and compound multinomial) for estimating classification indices when the observed score distribution shows atypical patterns: (a) bimodality, (b) structural (i.e., systematic) bumpiness, or (c) structural zeros (i.e., no…

This article describes an extension to the use of heteroskedastic ordered probit (HETOP) models to estimate latent distributional parameters from grouped, ordered-categorical data by pooling across multiple waves of data. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in…

A simulation study was conducted to explore the impact of differential item functioning (DIF) on general factor difference estimation for bifactor, ordinal data. Common analysis misspecifications in which the generated bifactor data with DIF were fitted using models with equality constraints on noninvariant item parameters were compared under data…

This study investigated the extent to which class-specific parameter estimates are biased by the within-class normality assumption in nonnormal growth mixture modeling (GMM). Monte Carlo simulations for nonnormal GMM were conducted to analyze and compare two strategies for obtaining unbiased parameter estimates: relaxing the within-class normality…

The mass participation in higher education has led to greater spending by governments and students which has increased the focus on graduate outcomes. In England, the Office for Students (OfS) is planning to take regulatory action, using the Proceed metric, against universities and their courses which do not have 60% of students with positive…

Educators use various statistical techniques to explain relationships between latent and observable variables. One way to model these relationships is to use Bayesian networks as a scoring model. However, adjusting the conditional probability tables (CPT-parameters) to fit a set of observations is still a challenge when using Bayesian networks. A…

A simulation study was conducted to investigate the model size effect when confirmatory factor analysis (CFA) models include many ordinal items. CFA models including between 15 and 120 ordinal items were analyzed with mean- and variance-adjusted weighted least squares to determine how varying sample size, number of ordered categories, and…

The authors examined the distributional properties of 3 improvement-over-chance, I, effect sizes each derived from linear and quadratic predictive discriminant analysis and from logistic regression analysis for the 2-group univariate classification. These 3 classification methods (3 levels) were studied under varying levels of data conditions,…

The current study investigated how between-subject and within-subject variance-covariance structures affected the detection of a finite mixture of unobserved subpopulations and parameter recovery of growth mixture models in the context of linear mixed-effects models. A simulation study was conducted to evaluate the impact of variance-covariance…