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Lientje Maas; Matthew J. Madison; Matthieu J. S. Brinkhuis – Grantee Submission, 2024
Diagnostic classification models (DCMs) are psychometric models that yield probabilistic classifications of respondents according to a set of discrete latent variables. The current study examines the recently introduced one-parameter log-linear cognitive diagnosis model (1-PLCDM), which has increased interpretability compared with general DCMs due…
Descriptors: Clinical Diagnosis, Classification, Models, Psychometrics
Daniel McNeish; Patrick D. Manapat – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A recent review found that 11% of published factor models are hierarchical models with second-order factors. However, dedicated recommendations for evaluating hierarchical model fit have yet to emerge. Traditional benchmarks like RMSEA <0.06 or CFI >0.95 are often consulted, but they were never intended to generalize to hierarchical models.…
Descriptors: Factor Analysis, Goodness of Fit, Hierarchical Linear Modeling, Benchmarking
Kathleen Lynne Lane; Katie Scarlett Lane Pelton; Nathan Allen Lane; Mark Matthew Buckman; Wendy Peia Oakes; Kandace Fleming; Rebecca E. Swinburne Romine; Emily D. Cantwell – Behavioral Disorders, 2025
We report findings of this replication study, examining the internalizing subscale (SRSS-I4) of the revised version of the Student Risk Screening Scale for Internalizing and Externalizing behavior (SRSS-IE 9) and the internalizing subscale of the Teacher Report Form (TRF). Using the sample from 13 elementary schools across three U.S. states with…
Descriptors: Data Analysis, Decision Making, Data Use, Measures (Individuals)
Comparing the Cost-Accuracy Ratios of Multiple Approaches to Reading Screening in Elementary Schools
Courtenay A. Barrett; Lindy J. Johnson; Adrea J. Truckenmiller; Amanda M. VanDerHeyden – Remedial and Special Education, 2024
U.S. elementary schools administer reading screeners to identify students in need of remedial instruction. However, the administration of additional assessments comes with a cost. It is unclear the extent to which multiple types of reading screeners warrant the increase in resources that could be used for instruction. This study compared…
Descriptors: Elementary School Students, Grade 3, Costs, Accuracy
Christine M. White; Christopher Schatschneider – Contemporary School Psychology, 2024
Universal screening to predict students' risk for reading problems is a foundational component of the Multi-Tiered Systems of Support framework and is required by law in many US states. School or district administrators are tasked with selecting screening assessments that are both technically adequate and feasible given the resources of their…
Descriptors: Screening Tests, Reading Tests, Reading Difficulties, Classification
Zeyu Xu – AERA Online Paper Repository, 2024
Children's math performance is strongly correlated with later life outcomes, but early gaps in math skills are stubbornly difficult to close. It is therefore important to identify student math needs early. Using Grade 1-3 student records from Kentucky public schools, the study finds that typically recommended cut scores for widely used early grade…
Descriptors: Mathematics Skills, Mathematics Achievement, Mathematics Education, Elementary School Mathematics
Kathleen Lynne Lane; Nathan Allen Lane; Mark Matthew Buckman; Katie Scarlett Lane Pelton; Kandace Fleming; Rebecca E. Swinburne Romine – Behavioral Disorders, 2025
We report the results of a convergent validity study examining the externalizing subscale (SRSS-E5, five items) of the adapted Student Risk Screening Scale for Internalizing and Externalizing (SRSS-IE 9) with the externalizing subscale of the Teacher Report Form (TRF) with two samples of K-12 students. Results of logistic regression and receiver…
Descriptors: Data Analysis, Decision Making, Data Use, Test Validity
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
Nami Shin – Educational Assessment, 2024
In 2006-2007, California revised its English language proficiency (ELP) assessment, the California English Language Development Test (CELDT), which resulted in more stringent criteria and higher cut scores for meeting proficiency. Using regression discontinuity designs and a difference-in-differences approach, this study examines the effects of…
Descriptors: Classification, English Language Learners, Language Proficiency, Language Tests