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Dardick, William R.; Mislevy, Robert J. – Educational and Psychological Measurement, 2016
A new variant of the iterative "data = fit + residual" data-analytical approach described by Mosteller and Tukey is proposed and implemented in the context of item response theory psychometric models. Posterior probabilities from a Bayesian mixture model of a Rasch item response theory model and an unscalable latent class are expressed…
Descriptors: Bayesian Statistics, Probability, Data Analysis, Item Response Theory
Marron, Megan M.; Wahed, Abdus S. – Journal of Statistics Education, 2016
Missing data mechanisms, methods of handling missing data, and the potential impact of missing data on study results are usually not taught until graduate school. However, the appropriate handling of missing data is fundamental to biomedical research and should be introduced earlier on in a student's education. The Summer Institute for Training in…
Descriptors: Summer Programs, Undergraduate Students, Data, Statistics
Fu, Jianbin; Zapata, Diego; Mavronikolas, Elia – ETS Research Report Series, 2014
Simulation or game-based assessments produce outcome data and process data. In this article, some statistical models that can potentially be used to analyze data from simulation or game-based assessments are introduced. Specifically, cognitive diagnostic models that can be used to estimate latent skills from outcome data so as to scale these…
Descriptors: Simulation, Evaluation Methods, Games, Data Collection
Verkuilen, Jay; Smithson, Michael – Journal of Educational and Behavioral Statistics, 2012
Doubly bounded continuous data are common in the social and behavioral sciences. Examples include judged probabilities, confidence ratings, derived proportions such as percent time on task, and bounded scale scores. Dependent variables of this kind are often difficult to analyze using normal theory models because their distributions may be quite…
Descriptors: Responses, Regression (Statistics), Statistical Analysis, Models
D'Mello, Sidney; Olney, Andrew; Person, Natalie – Journal of Educational Data Mining, 2010
We present a method to automatically detect collaborative patterns of student and tutor dialogue moves. The method identifies significant two-step excitatory transitions between dialogue moves, integrates the transitions into a directed graph representation, and generates and tests data-driven hypotheses from the directed graph. The method was…
Descriptors: Tutors, Interpersonal Communication, Discourse Analysis, Intelligent Tutoring Systems
Using Data Augmentation and Markov Chain Monte Carlo for the Estimation of Unfolding Response Models
Johnson, Matthew S.; Junker, Brian W. – Journal of Educational and Behavioral Statistics, 2003
Unfolding response models, a class of item response theory (IRT) models that assume a unimodal item response function (IRF), are often used for the measurement of attitudes. Verhelst and Verstralen (1993)and Andrich and Luo (1993) independently developed unfolding response models by relating the observed responses to a more common monotone IRT…
Descriptors: Markov Processes, Item Response Theory, Computation, Data Analysis