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Joshua B. Gilbert – Annenberg Institute for School Reform at Brown University, 2024
When analyzing treatment effects on test scores, researchers face many choices and competing guidance for scoring tests and modeling results. This study examines the impact of scoring choices through simulation and an empirical application. Results show that estimates from multiple methods applied to the same data will vary because two-step models…
Descriptors: Scores, Statistical Bias, Statistical Inference, Scoring
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Onur Demirkaya; Sharon Frey; Sid Sharairi; JongPil Kim – International Electronic Journal of Elementary Education, 2025
This study compares latent profiles derived from student subgroups of varying levels of mathematical skills defined by achievement and ability assessment scores. Achievement and ability cut scores for identifying students at both ends of the mathematics spectrum were applied and the resulting latent profiles within each condition were compared.…
Descriptors: Profiles, Statistical Analysis, Academic Achievement, Mathematics Achievement
Joshua B. Gilbert – Annenberg Institute for School Reform at Brown University, 2022
This simulation study examines the characteristics of the Explanatory Item Response Model (EIRM) when estimating treatment effects when compared to classical test theory (CTT) sum and mean scores and item response theory (IRT)-based theta scores. Results show that the EIRM and IRT theta scores provide generally equivalent bias and false positive…
Descriptors: Item Response Theory, Models, Test Theory, Computation
Christian T. Doabler; Ben Clarke; Derek Kosty; Marah Sutherland; Jessica E. Turtura; Allison R. Firestone; Georgia L. Kimmel; Patrick Brott; Tasia L. Brafford; Nancy J. Nelson Fien; Keith Smolkowski; Kathleen Jungjohann – Grantee Submission, 2022
Measurement and statistical investigation are areas of mathematics visibly neglected in educational intervention research, particularly studies involving students with or at risk for mathematics difficulties (MD). This shortage is concerning given the importance these areas hold in students' pursuit of mathematical proficiency. This study…
Descriptors: Measurement, Statistical Analysis, Grade 2, Elementary School Students
Peer reviewed Peer reviewed
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Christian T. Doabler; Ben Clarke; Derek Kosty; Marah Sutherland; Jessica E. Turtura; Allison R. Firestone; Georgia L. Kimmel; Patrick Brott; Tasia L. Brafford; Nancy J. Nelson Fien; Keith Smolkowski; Kathleen Jungjohann – Journal of Educational Psychology, 2022
Measurement and statistical investigation are areas of mathematics visibly neglected in educational intervention research, particularly studies involving students with or at risk for mathematics difficulties (MD). This shortage is concerning given the importance these areas hold in students' pursuit of mathematical proficiency. This study…
Descriptors: Measurement, Statistical Analysis, Grade 2, Elementary School Students
Bucknor Rodney, Camille Aretha – ProQuest LLC, 2022
The COVID-19 pandemic provided an opportunity to explore how different modes of learning may impact student achievement. Little research has been conducted regarding how the pandemic may have affected students' reading skills. The problem addressed in this study was that the effects of varying and inconsistent learning environments for Title I K-2…
Descriptors: Statistical Analysis, Outcomes of Education, Elementary School Students, Pandemics
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Erbeli, Florina; He, Kai; Cheek, Connor; Rice, Marianne; Qian, Xiaoning – Scientific Studies of Reading, 2023
Purpose: Researchers have developed a constellation model of decodingrelated reading disabilities (RD) to improve the RD risk determination. The model's hallmark is its inclusion of various RD indicators to determine RD risk. Classification methods such as logistic regression (LR) might be one way to determine RD risk within the constellation…
Descriptors: At Risk Students, Reading Difficulties, Classification, Comparative Analysis