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Showing 1 to 15 of 556 results Save | Export
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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
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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
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Sales, Adam C.; Hansen, Ben B.; Rowan, Brian – Journal of Educational and Behavioral Statistics, 2018
In causal matching designs, some control subjects are often left unmatched, and some covariates are often left unmodeled. This article introduces "rebar," a method using high-dimensional modeling to incorporate these commonly discarded data without sacrificing the integrity of the matching design. After constructing a match, a researcher…
Descriptors: Computation, Prediction, Models, Data
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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
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Yang, Ji Seung; Zheng, Xiaying – Journal of Educational and Behavioral Statistics, 2018
The purpose of this article is to introduce and review the capability and performance of the Stata item response theory (IRT) package that is available from Stata v.14, 2015. Using a simulated data set and a publicly available item response data set extracted from Programme of International Student Assessment, we review the IRT package from…
Descriptors: Item Response Theory, Item Analysis, Computer Software, Statistical Analysis
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Nestler, Steffen – Journal of Educational and Behavioral Statistics, 2018
The social relations model (SRM) is a mathematical model that can be used to analyze interpersonal judgment and behavior data. Typically, the SRM is applied to one (i.e., univariate SRM) or two variables (i.e., bivariate SRM), and parameter estimates are obtained by employing an analysis of variance method. Here, we present an extension of the SRM…
Descriptors: Mathematical Models, Interpersonal Relationship, Maximum Likelihood Statistics, Computation
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Casabianca, Jodi M.; Lewis, Charles – Journal of Educational and Behavioral Statistics, 2018
The null hypothesis test used in differential item functioning (DIF) detection tests for a subgroup difference in item-level performance--if the null hypothesis of "no DIF" is rejected, the item is flagged for DIF. Conversely, an item is kept in the test form if there is insufficient evidence of DIF. We present frequentist and empirical…
Descriptors: Test Bias, Hypothesis Testing, Bayesian Statistics, Statistical Analysis
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Leckie, George – Journal of Educational and Behavioral Statistics, 2018
The traditional approach to estimating the consistency of school effects across subject areas and the stability of school effects across time is to fit separate value-added multilevel models to each subject or cohort and to correlate the resulting empirical Bayes predictions. We show that this gives biased correlations and these biases cannot be…
Descriptors: Value Added Models, Reliability, Statistical Bias, Computation
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Wang, Chun; Xu, Gongjun; Shang, Zhuoran; Kuncel, Nathan – Journal of Educational and Behavioral Statistics, 2018
The modern web-based technology greatly popularizes computer-administered testing, also known as online testing. When these online tests are administered continuously within a certain "testing window," many items are likely to be exposed and compromised, posing a type of test security concern. In addition, if the testing time is limited,…
Descriptors: Computer Assisted Testing, Cheating, Guessing (Tests), Item Response Theory
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Choe, Edison M.; Kern, Justin L.; Chang, Hua-Hua – Journal of Educational and Behavioral Statistics, 2018
Despite common operationalization, measurement efficiency of computerized adaptive testing should not only be assessed in terms of the number of items administered but also the time it takes to complete the test. To this end, a recent study introduced a novel item selection criterion that maximizes Fisher information per unit of expected response…
Descriptors: Computer Assisted Testing, Reaction Time, Item Response Theory, Test Items
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Moerbeek, Mirjam; Safarkhani, Maryam – Journal of Educational and Behavioral Statistics, 2018
Data from cluster randomized trials do not always have a pure hierarchical structure. For instance, students are nested within schools that may be crossed by neighborhoods, and soldiers are nested within army units that may be crossed by mental health-care professionals. It is important that the random cross-classification is taken into account…
Descriptors: Randomized Controlled Trials, Classification, Research Methodology, Military Personnel
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Chan, Wendy – Journal of Educational and Behavioral Statistics, 2018
Policymakers have grown increasingly interested in how experimental results may generalize to a larger population. However, recently developed propensity score-based methods are limited by small sample sizes, where the experimental study is generalized to a population that is at least 20 times larger. This is particularly problematic for methods…
Descriptors: Computation, Generalization, Probability, Sample Size
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Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2018
Multiple imputation (MI) can be used to address missing data at Level 2 in multilevel research. In this article, we compare joint modeling (JM) and the fully conditional specification (FCS) of MI as well as different strategies for including auxiliary variables at Level 1 using either their manifest or their latent cluster means. We show with…
Descriptors: Statistical Analysis, Data, Comparative Analysis, Hierarchical Linear Modeling
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Kovalchik, Stephanie A.; Martino, Steven C.; Collins, Rebecca L.; Shadel, William G.; D'Amico, Elizabeth J.; Becker, Kirsten – Journal of Educational and Behavioral Statistics, 2018
Ecological momentary assessment (EMA) is a popular assessment method in psychology that aims to capture events, emotions, and cognitions in real time, usually repeatedly throughout the day. Because EMA typically involves more intensive monitoring than traditional assessment methods, missing data are commonly an issue and this missingness may bias…
Descriptors: Probability, Statistical Bias, Holistic Approach, Evaluation Methods
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Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2018
Wollack, Cohen, and Eckerly suggested the "erasure detection index" (EDI) to detect fraudulent erasures for individual examinees. Wollack and Eckerly extended the EDI to detect fraudulent erasures at the group level. The EDI at the group level was found to be slightly conservative. This article suggests two modifications of the EDI for…
Descriptors: Deception, Identification, Testing Problems, Cheating
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