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Showing 121 to 135 of 705 results Save | Export
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Kim, Yongnam – Journal of Educational and Behavioral Statistics, 2019
Suppression effects in multiple linear regression are one of the most elusive phenomena in the educational and psychological measurement literature. The question is, How can including a variable, which is completely unrelated to the criterion variable, in regression models significantly increase the predictive power of the regression models? In…
Descriptors: Multiple Regression Analysis, Causal Models, Predictor Variables
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Lai, Mark H. C. – Journal of Educational and Behavioral Statistics, 2019
Previous studies have detailed the consequence of ignoring a level of clustering in multilevel models with straightly hierarchical structures and have proposed methods to adjust for the fixed effect standard errors (SEs). However, in behavioral and social science research, there are usually two or more crossed clustering levels, such as when…
Descriptors: Error of Measurement, Hierarchical Linear Modeling, Least Squares Statistics, Statistical Bias
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Zhan, Peida; Jiao, Hong; Man, Kaiwen; Wang, Lijun – Journal of Educational and Behavioral Statistics, 2019
In this article, we systematically introduce the just another Gibbs sampler (JAGS) software program to fit common Bayesian cognitive diagnosis models (CDMs) including the deterministic inputs, noisy "and" gate model; the deterministic inputs, noisy "or" gate model; the linear logistic model; the reduced reparameterized unified…
Descriptors: Bayesian Statistics, Computer Software, Models, Test Items
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Hayes, Timothy – Journal of Educational and Behavioral Statistics, 2019
Multiple imputation is a popular method for addressing data that are presumed to be missing at random. To obtain accurate results, one's imputation model must be congenial to (appropriate for) one's intended analysis model. This article reviews and demonstrates two recent software packages, Blimp and jomo, to multiply impute data in a manner…
Descriptors: Computer Software Evaluation, Computer Software Reviews, Hierarchical Linear Modeling, Data Analysis
Choi, Kilchan; Kim, Jinok – Journal of Educational and Behavioral Statistics, 2019
This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual assessment scores over grades for students who are nested within cohorts within schools, the LVR-HM4 attempts to simultaneously model two types of…
Descriptors: Regression (Statistics), Hierarchical Linear Modeling, Longitudinal Studies, Cohort Analysis
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Loeb, Susanna; Christian, Michael S.; Hough, Heather; Meyer, Robert H.; Rice, Andrew B.; West, Martin R. – Journal of Educational and Behavioral Statistics, 2019
Measures of school-level growth in student outcomes are common tools for assessing the impacts of schools. The vast majority of these measures use standardized tests as the outcome of interest, even though emerging evidence demonstrates the importance of social-emotional learning (SEL). In this article, we present results from using the first…
Descriptors: Social Development, Emotional Development, Student Surveys, Institutional Characteristics
Hedges, Larry V.; Schauer, Jacob M. – Journal of Educational and Behavioral Statistics, 2019
The problem of assessing whether experimental results can be replicated is becoming increasingly important in many areas of science. It is often assumed that assessing replication is straightforward: All one needs to do is repeat the study and see whether the results of the original and replication studies agree. This article shows that the…
Descriptors: Replication (Evaluation), Research Design, Research Methodology, Program Evaluation
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Guo, Hongwen; Zhang, Mo; Deane, Paul; Bennett, Randy E. – Journal of Educational and Behavioral Statistics, 2019
We used an unobtrusive approach, keystroke logging, to examine students' cognitive states during essay writing. Based on data contained in the logs, we classified writing process data into three states: text production, long pause, and editing. We used semi-Markov processes to model the sequences of writing states and compared the state transition…
Descriptors: Writing Processes, Cognitive Processes, Essays, Keyboarding (Data Entry)
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Jiang, Yu; Zhang, Jiahui; Xin, Tao – Journal of Educational and Behavioral Statistics, 2019
This article is an overview of the National Assessment of Education Quality (NAEQ) of China in reading, mathematics, sciences, arts, physical education, and moral education at Grades 4 and 8. After a review of the background and history of NAEQ, we present the assessment framework with students' holistic development at the core and the design for…
Descriptors: Foreign Countries, Educational Quality, Educational Improvement, National Competency Tests
Oranje, Andreas; Kolstad, Andrew – Journal of Educational and Behavioral Statistics, 2019
The design and psychometric methodology of the National Assessment of Educational Progress (NAEP) is constantly evolving to meet the changing interests and demands stemming from a rapidly shifting educational landscape. NAEP has been built on strong research foundations that include conducting extensive evaluations and comparisons before new…
Descriptors: National Competency Tests, Psychometrics, Statistical Analysis, Computation
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von Davier, Matthias; Khorramdel, Lale; He, Qiwei; Shin, Hyo Jeong; Chen, Haiwen – Journal of Educational and Behavioral Statistics, 2019
International large-scale assessments (ILSAs) transitioned from paper-based assessments to computer-based assessments (CBAs) facilitating the use of new item types and more effective data collection tools. This allows implementation of more complex test designs and to collect process and response time (RT) data. These new data types can be used to…
Descriptors: International Assessment, Computer Assisted Testing, Psychometrics, Item Response Theory
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Martin, Michael O.; Mullis, Ina V. S. – Journal of Educational and Behavioral Statistics, 2019
International large-scale assessments of student achievement such as International Association for the Evaluation of Educational Achievement's Trends in International Mathematics and Science Study (TIMSS) and Progress in International Reading Literacy Study and Organization for Economic Cooperation and Development's Program for International…
Descriptors: Achievement Tests, International Assessment, Mathematics Tests, Science Achievement
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Bergner, Yoav; von Davier, Alina A. – Journal of Educational and Behavioral Statistics, 2019
This article reviews how National Assessment of Educational Progress (NAEP) has come to collect and analyze data about cognitive and behavioral processes (process data) in the transition to digital assessment technologies over the past two decades. An ordered five-level structure is proposed for describing the uses of process data. The levels in…
Descriptors: National Competency Tests, Data Collection, Data Analysis, Cognitive Processes
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Matta, Tyler H.; Soland, James – Journal of Educational and Behavioral Statistics, 2019
The development of academic English proficiency and the time it takes to reclassify to fluent English proficient status are key issues in English learner (EL) policy. This article develops a shared random effects model (SREM) to estimate English proficiency development and time to reclassification simultaneously, treating student-specific random…
Descriptors: English Language Learners, Language Proficiency, Classification, Language Fluency
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Culpepper, Steven Andrew; Chen, Yinghan – Journal of Educational and Behavioral Statistics, 2019
Exploratory cognitive diagnosis models (CDMs) estimate the Q matrix, which is a binary matrix that indicates the attributes needed for affirmative responses to each item. Estimation of Q is an important next step for improving classifications and broadening application of CDMs. Prior research primarily focused on an exploratory version of the…
Descriptors: Cognitive Measurement, Models, Bayesian Statistics, Computation
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