NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
No Child Left Behind Act 20012
What Works Clearinghouse Rating
Showing 1 to 15 of 572 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Vegetabile, Brian G.; Stout-Oswald, Stephanie A.; Davis, Elysia Poggi; Baram, Tallie Z.; Stern, Hal S. – Journal of Educational and Behavioral Statistics, 2019
Predictability of behavior is an important characteristic in many fields including biology, medicine, marketing, and education. When a sequence of actions performed by an individual can be modeled as a stationary time-homogeneous Markov chain the predictability of the individual's behavior can be quantified by the entropy rate of the process. This…
Descriptors: Markov Processes, Prediction, Behavior, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Hao, Jiangang; Ho, Tin Kam – Journal of Educational and Behavioral Statistics, 2019
Machine learning is a popular topic in data analysis and modeling. Many different machine learning algorithms have been developed and implemented in a variety of programming languages over the past 20 years. In this article, we first provide an overview of machine learning and clarify its difference from statistical inference. Then, we review…
Descriptors: Artificial Intelligence, Statistical Inference, Data Analysis, Programming Languages
Peer reviewed Peer reviewed
Direct linkDirect link
Wang, Shiyu; Yang, Yan; Culpepper, Steven Andrew; Douglas, Jeffrey A. – Journal of Educational and Behavioral Statistics, 2018
A family of learning models that integrates a cognitive diagnostic model and a higher-order, hidden Markov model in one framework is proposed. This new framework includes covariates to model skill transition in the learning environment. A Bayesian formulation is adopted to estimate parameters from a learning model. The developed methods are…
Descriptors: Skill Development, Cognitive Measurement, Cognitive Processes, Markov Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Philipp, Michel; Strobl, Carolin; de la Torre, Jimmy; Zeileis, Achim – Journal of Educational and Behavioral Statistics, 2018
Cognitive diagnosis models (CDMs) are an increasingly popular method to assess mastery or nonmastery of a set of fine-grained abilities in educational or psychological assessments. Several inference techniques are available to quantify the uncertainty of model parameter estimates, to compare different versions of CDMs, or to check model…
Descriptors: Computation, Error of Measurement, Models, Cognitive Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Hong, Guanglei; Qin, Xu; Yang, Fan – Journal of Educational and Behavioral Statistics, 2018
Through a sensitivity analysis, the analyst attempts to determine whether a conclusion of causal inference could be easily reversed by a plausible violation of an identification assumption. Analytic conclusions that are harder to alter by such a violation are expected to add a higher value to scientific knowledge about causality. This article…
Descriptors: Statistical Inference, Probability, Statistical Bias, Statistical Analysis
Previous Page | Next Page ยป
Pages: 1  |  2  |  3  |  4  |  5  |  6  |  7  |  8  |  9  |  10  |  11  |  ...  |  39