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Zhenchang Xia; Nan Dong; Jia Wu; Chuanguo Ma – IEEE Transactions on Learning Technologies, 2024
As an excellent means of improving students' effective learning, knowledge tracking can assess the level of knowledge mastery and discover latent learning patterns based on students' historical learning evaluation of related questions. The advantage of knowledge tracking is that it can better organize and adjust students' learning plans, provide…
Descriptors: Graphs, Artificial Intelligence, Multivariate Analysis, Prediction
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Cerullo, Enzo; Jones, Hayley E.; Carter, Olivia; Quinn, Terry J.; Cooper, Nicola J.; Sutton, Alex J. – Research Synthesis Methods, 2022
Standard methods for the meta-analysis of medical tests, without assuming a gold standard, are limited to dichotomous data. Multivariate probit models are used to analyse correlated dichotomous data, and can be extended to model ordinal data. Within the context of an imperfect gold standard, they have previously been used for the analysis of…
Descriptors: Meta Analysis, Test Format, Medicine, Standards
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DeMars, Christine E. – Educational and Psychological Measurement, 2016
Partially compensatory models may capture the cognitive skills needed to answer test items more realistically than compensatory models, but estimating the model parameters may be a challenge. Data were simulated to follow two different partially compensatory models, a model with an interaction term and a product model. The model parameters were…
Descriptors: Item Response Theory, Models, Thinking Skills, Test Items
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Tutz, Gerhard; Berger, Moritz – Journal of Educational and Behavioral Statistics, 2016
Heterogeneity in response styles can affect the conclusions drawn from rating scale data. In particular, biased estimates can be expected if one ignores a tendency to middle categories or to extreme categories. An adjacent categories model is proposed that simultaneously models the content-related effects and the heterogeneity in response styles.…
Descriptors: Response Style (Tests), Rating Scales, Data Interpretation, Statistical Bias
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Lang, Kyle M.; Little, Todd D. – International Journal of Behavioral Development, 2014
We present a new paradigm that allows simplified testing of multiparameter hypotheses in the presence of incomplete data. The proposed technique is a straight-forward procedure that combines the benefits of two powerful data analytic tools: multiple imputation and nested-model ?2 difference testing. A Monte Carlo simulation study was conducted to…
Descriptors: Hypothesis Testing, Data Analysis, Error of Measurement, Computation
McKoon, Gai; Ratcliff, Roger – Grantee Submission, 2016
Millions of adults in the United States lack the necessary literacy skills for most living wage jobs. For students from adult learning classes, we used a lexical decision task to measure their knowledge of words and we used a decision-making model (Ratcliff's, 1978, diffusion model) to abstract the mechanisms underlying their performance from…
Descriptors: Reading Skills, Psycholinguistics, Memory, Decision Making
Ngan, Chun-Kit – ProQuest LLC, 2013
Making decisions over multivariate time series is an important topic which has gained significant interest in the past decade. A time series is a sequence of data points which are measured and ordered over uniform time intervals. A multivariate time series is a set of multiple, related time series in a particular domain in which domain experts…
Descriptors: Multivariate Analysis, Time, Intervals, Decision Making
Gleason, Michael – ProQuest LLC, 2013
Background: Breast cancer (BC), the most common cancer diagnosed in women in the United States, is a heterogeneous disease in which age-specific incidence rates (ASIRs) differ by race and mortality rates are higher in blacks than whites. Goals: (i) understand the reasons for the black-to-white ethnic crossover in the ASIRs; (ii) formulate a…
Descriptors: Cancer, Females, Racial Differences, African Americans
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries