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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Jorge Salas – Journal of Educational Measurement, 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
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
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Daniel Kasper; Katrin Schulz-Heidorf; Knut Schwippert – Sociological Methods & Research, 2024
In this article, we extend Liao's test for across-group comparisons of the fixed effects from the generalized linear model to the fixed and random effects of the generalized linear mixed model (GLMM). Using as our basis the Wald statistic, we developed an asymptotic test statistic for across-group comparisons of these effects. The test can be…
Descriptors: Models, Achievement Tests, Foreign Countries, International Assessment
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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
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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
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Morinaj, Julia; Scharf, Jan; Grecu, Alyssa; Hadjar, Andreas; Hascher, Tina; Marcin, Kaja – Frontline Learning Research, 2017
Early identification of school alienation is of great importance for students' educational outcomes and successful participation in society. This study examined the psychometric characteristics of a newly developed assessment instrument, the School Alienation Scale (SALS), to measure school alienation among primary and secondary school students.…
Descriptors: Foreign Countries, Comparative Education, Alienation, Learner Engagement
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Spilt, Jantine L.; Koomen, Helma M. Y.; Harrison, Linda J. – Developmental Psychology, 2015
This longitudinal study examined developmental links between closeness in teacher-child relationships and children's receptive language ability from the end of the preschool years into the early elementary years, while controlling for changes in peer interaction quality and child behavioral functioning. The sample included children and their…
Descriptors: Language Acquisition, Teacher Student Relationship, Preschool Children, Preschool Teachers
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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
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Berebitsky, Dan; Goddard, Roger D.; Carlisle, Joanne F. – Teachers College Record, 2014
Background/Context: Little research has directly examined whether principal leadership can increase the degree to which teachers work together regularly in focused ways around content. Prior research has shown that reform efforts seeking to alter the process of teaching can be successful if teachers collaborate to build capacity and improve…
Descriptors: Teacher Administrator Relationship, Instructional Leadership, Teacher Collaboration, Capacity Building
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Harring, Jeffrey R. – Journal of Educational and Behavioral Statistics, 2009
The nonlinear mixed effects model for continuous repeated measures data has become an increasingly popular and versatile tool for investigating nonlinear longitudinal change in observed variables. In practice, for each individual subject, multiple measurements are obtained on a single response variable over time or condition. This structure can be…
Descriptors: Regression (Statistics), Computation, Measurement, Models
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Schochet, Peter Z. – National Center for Education Evaluation and Regional Assistance, 2009
This paper examines the estimation of two-stage clustered RCT designs in education research using the Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for the study population (the…
Descriptors: Control Groups, Causal Models, Statistical Significance, Computation
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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