Categorical growth models describe examinee growth in terms of performance-level category transitions, which implies that some percentage of examinees will be misclassified. This paper introduces a new procedure for estimating the classification accuracy of categorical growth models, based on Rudner's classification accuracy index for item…

Growth mixture models (GMMs) are a popular method to identify latent classes of growth trajectories. One shortcoming of GMMs is nonconvergence, which often leads researchers to apply covariance equality constraints to simplify estimation, though this may be a dubious assumption. Alternative model specifications have been proposed to reduce…

Growth mixture models (GMMs) are a popular method to uncover heterogeneity in growth trajectories. Harnessing the power of GMMs in applications is difficult given the prevalence of nonconvergence when fitting GMMs to empirical data. GMMs are rooted in the random effect tradition and nonconvergence often leads researchers to modify their intended…

During the past decade, cognitive diagnostic models (CDMs) have become prevalent in providing diagnostic information for learning. Cognitive diagnostic models have generally focused on single cross-sectional time points. However, longitudinal assessments have been commonly used in education to assess students' learning progress as well as…

Student growth percentiles (SGPs) are currently used by several states and school districts to provide information about individual students as well as to evaluate teachers, schools, and school districts. For SGPs to be defensible for these purposes, they should be reliable. In this study, we examine the amount of systematic and random error in…

Providing diagnostic feedback about growth is crucial to formative decisions such as targeted remedial instructions or interventions. This article proposed a longitudinal higher-order diagnostic classification modeling approach for measuring growth. The new modeling approach is able to provide quantitative values of overall and individual growth…

Statewide accountability programs are incorporating academic growth estimates for general assessments. This transition focuses attention on modeling growth for students with significant cognitive disabilities (SWSCD) who take alternate assessments based on alternate achievement standards (AA-AAS), as most states attempt to structure their AA-AAS…

Our purpose was to examine different approaches to modeling the time-varying nature of exceptionality classification. Using longitudinal data from one state's mathematics achievement test for 28,829 students in Grades 3 to 8, we describe the reclassification rate within special education and between general and special education, and compare four…