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Showing 1 to 15 of 583 results Save | Export
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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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Ma, Wenchao; de la Torre, Jimmy – Journal of Educational and Behavioral Statistics, 2019
Solving a constructed-response item usually requires successfully performing a sequence of tasks. Each task could involve different attributes, and those required attributes may be "condensed" in various ways to produce the responses. The sequential generalized deterministic input noisy "and" gate model is a general cognitive…
Descriptors: Test Items, Cognitive Measurement, Models, Hypothesis Testing
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Kim, Minjung; Hsu, Hsien-Yuan – Journal of Educational and Behavioral Statistics, 2019
Given the natural hierarchical structure in school-setting data, multilevel modeling (MLM) has been widely employed in education research using a number of different statistical software packages. The purpose of this article is to review a recent feature of Stat-JR, the statistical analysis assistants (SAAs) embedded in Stat-JR (Version 1.0.5),…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Computer Software, Computer Software Evaluation
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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
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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
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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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Parsons, Eric; Koedel, Cory; Tan, Li – Journal of Educational and Behavioral Statistics, 2019
We study the relative performance of two policy-relevant value-added models--a one-step fixed effect model and a two-step aggregated residuals model--using a simulated data set well grounded in the value-added literature. A key feature of our data generating process is that student achievement depends on a continuous measure of economic…
Descriptors: Value Added Models, Economically Disadvantaged, Academic Achievement, Low Income Students
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Barrett, Michelle D.; van der Linden, Wim J. – Journal of Educational and Behavioral Statistics, 2019
Parameter linking in item response theory is generally necessary to adjust for differences between the true values for the same item and ability parameters due to the use of different identifiability restrictions in different calibrations. The research reported in this article explores a precision-weighted (PW) approach to the problem of…
Descriptors: Item Response Theory, Computation, Error of Measurement, Test Items
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Astivia, Oscar L. Olvera; Zumbo, Bruno D. – Journal of Educational and Behavioral Statistics, 2019
The Vale and Maurelli algorithm is a widely used method that allows researchers to generate multivariate, nonnormal data with user-specified levels of skewness, excess kurtosis, and a correlation structure. Before obtaining the desired correlation structure, a transitional step requires the user to calculate the roots of a cubic polynomial…
Descriptors: Equations (Mathematics), Correlation, Statistical Analysis, Mathematics
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Sweet, Tracy M. – Journal of Educational and Behavioral Statistics, 2019
There are some educational interventions aimed at changing the ways in which individuals interact, and social networks are particularly useful for quantifying these changes. For many of these interventions, the ultimate goal is to change some outcome of interest such as teacher quality or student achievement, and social networks act as a natural…
Descriptors: Interaction, Intervention, Mediation Theory, Social Networks
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Zhan, Peida; Jiao, Hong; Liao, Dandan; Li, Feiming – Journal of Educational and Behavioral Statistics, 2019
Providing diagnostic feedback about growth is crucial to formative decisions such as targeted remedial instructions or interventions. This article proposed a longitudinal higher-order diagnostic classification modeling approach for measuring growth. The new modeling approach is able to provide quantitative values of overall and individual growth…
Descriptors: Classification, Growth Models, Educational Diagnosis, Models
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Patton, Jeffrey M.; Cheng, Ying; Hong, Maxwell; Diao, Qi – Journal of Educational and Behavioral Statistics, 2019
In psychological and survey research, the prevalence and serious consequences of careless responses from unmotivated participants are well known. In this study, we propose to iteratively detect careless responders and cleanse the data by removing their responses. The careless responders are detected using person-fit statistics. In two simulation…
Descriptors: Test Items, Response Style (Tests), Identification, Computation
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