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Kyle T. Turner; George Engelhard Jr. – Journal of Experimental Education, 2024
The purpose of this study is to demonstrate clustering methods within a functional data analysis (FDA) framework for identifying subgroups of individuals that may be exhibiting categories of misfit. Person response functions (PRFs) estimated within a FDA framework (FDA-PRFs) provide graphical displays that can aid in the identification of persons…
Descriptors: Data Analysis, Multivariate Analysis, Individual Characteristics, Behavior
Liqun Yin; Ummugul Bezirhan; Matthias von Davier – International Electronic Journal of Elementary Education, 2025
This paper introduces an approach that uses latent class analysis to identify cut scores (LCA-CS) and categorize respondents based on context scales derived from largescale assessments like PIRLS, TIMSS, and NAEP. Context scales use Likert scale items to measure latent constructs of interest and classify respondents into meaningful ordered…
Descriptors: Multivariate Analysis, Cutting Scores, Achievement Tests, Foreign Countries
David Bamat – Measurement: Interdisciplinary Research and Perspectives, 2024
The National Assessment of Educational Progress (NAEP) program only reports state-level subgroup results if it samples at least 62 students identifying with the subgroup. Since some subgroups constitute small proportions of many states' general student populations, these minority subgroups are seldom sufficiently sampled to meet this sample size…
Descriptors: Reading Achievement, Achievement Gap, Prediction, National Competency Tests