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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Jorge Salas – Grantee Submission, 2024
Despite the growing interest in incorporating response time data into item response models, there has been a lack of research investigating how the effect of speed on the probability of a correct response varies across different groups (e.g., experimental conditions) for various items (i.e., differential response time item analysis). Furthermore,…
Descriptors: Item Response Theory, Reaction Time, Models, Accuracy
Rijmen, Frank; Jeon, Minjeong; von Davier, Matthias; Rabe-Hesketh, Sophia – Journal of Educational and Behavioral Statistics, 2014
Second-order item response theory models have been used for assessments consisting of several domains, such as content areas. We extend the second-order model to a third-order model for assessments that include subdomains nested in domains. Using a graphical model framework, it is shown how the model does not suffer from the curse of…
Descriptors: Item Response Theory, Models, Educational Assessment, Computation
Martin, Andrew J.; Martin, Tamica G.; Evans, Paul – Journal of Psychoeducational Assessment, 2018
This study explored motivation and engagement among 585 Jamaican middle and high school students. Motivation and engagement were assessed via students' responses to the Motivation and Engagement Scale. Confirmatory factor analysis (CFA) found satisfactory fit, and by most measures, multigroup CFA demonstrated comparable factor structure for males…
Descriptors: Learner Engagement, Middle School Students, High School Students, Foreign Countries
Kearns, Devin M.; Steacy, Laura M.; Compton, Donald L.; Gilbert, Jennifer K.; Goodwin, Amanda P.; Cho, Eunsoo; Lindstrom, Esther R.; Collins, Alyson A. – Journal of Learning Disabilities, 2016
Comprehensive models of derived polymorphemic word recognition skill in developing readers, with an emphasis on children with reading difficulty (RD), have not been developed. The purpose of the present study was to model individual differences in polymorphemic word recognition ability at the item level among 5th-grade children (N = 173)…
Descriptors: Word Recognition, Reading Difficulties, Individual Differences, Grade 5
Lee, Christine S.; Hayes, Kathryn N.; Seitz, Jeffery; DiStefano, Rachelle; O'Connor, Dawn – International Journal of Science Education, 2016
Middle school has been documented as the period in which a drop in students' science interest and achievement occurs. This trend indicates a lack of motivation for learning science; however, little is known about how different aspects of motivation interact with student engagement and science learning outcomes. This study examines the…
Descriptors: Middle School Students, Science Instruction, Student Motivation, Science Interests
Jeon, Minjeong; Rabe-Hesketh, Sophia – Journal of Educational and Behavioral Statistics, 2012
In this article, the authors suggest a profile-likelihood approach for estimating complex models by maximum likelihood (ML) using standard software and minimal programming. The method works whenever setting some of the parameters of the model to known constants turns the model into a standard model. An important class of models that can be…
Descriptors: Maximum Likelihood Statistics, Computation, Models, Factor Structure
Cho, Sun-Joo; Cohen, Allan S.; Bottge, Brian – Grantee Submission, 2013
A multilevel latent transition analysis (LTA) with a mixture IRT measurement model (MixIRTM) is described for investigating the effectiveness of an intervention. The addition of a MixIRTM to the multilevel LTA permits consideration of both potential heterogeneity in students' response to instructional intervention as well as a methodology for…
Descriptors: Intervention, Item Response Theory, Statistical Analysis, Models
Vaughn, Sharon; Fletcher, Jack M. – Journal of Learning Disabilities, 2012
The authors summarize evidence from a multiyear study with secondary students with reading difficulties on (a) the potential efficacy of primary-level (Tier 1), secondary-level (Tier 2), and tertiary-level (Tier 3) interventions in remediating reading difficulties with middle school students, (b) the likelihood of resolving reading disabilities…
Descriptors: Evidence, Middle School Students, Reading Difficulties, Intervention
Sinharay, Sandip; von Davier, Matthias – ETS Research Report Series, 2005
The reporting methods used in large scale assessments such as the National Assessment of Educational Progress (NAEP) rely on a "latent regression model." The first component of the model consists of a "p"-scale IRT measurement model that defines the response probabilities on a set of cognitive items in "p" scales…
Descriptors: National Competency Tests, Regression (Statistics), Predictor Variables, Student Characteristics

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