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McNeish, Daniel – Journal of Experimental Education, 2018
Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…
Descriptors: Measures (Individuals), Nonparametric Statistics, Item Response Theory, Regression (Statistics)
Wind, Stefanie A. – Educational and Psychological Measurement, 2017
Molenaar extended Mokken's original probabilistic-nonparametric scaling models for use with polytomous data. These polytomous extensions of Mokken's original scaling procedure have facilitated the use of Mokken scale analysis as an approach to exploring fundamental measurement properties across a variety of domains in which polytomous ratings are…
Descriptors: Nonparametric Statistics, Scaling, Models, Item Response Theory
Wind, Stefanie A. – Educational Measurement: Issues and Practice, 2017
Mokken scale analysis (MSA) is a probabilistic-nonparametric approach to item response theory (IRT) that can be used to evaluate fundamental measurement properties with less strict assumptions than parametric IRT models. This instructional module provides an introduction to MSA as a probabilistic-nonparametric framework in which to explore…
Descriptors: Probability, Nonparametric Statistics, Item Response Theory, Scaling
Mao, Ye; Lin, Chen; Chi, Min – Journal of Educational Data Mining, 2018
Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…
Descriptors: Prediction, Pretests Posttests, Bayesian Statistics, Short Term Memory
Vuolo, Mike – Sociological Methods & Research, 2017
Often in sociology, researchers are confronted with nonnormal variables whose joint distribution they wish to explore. Yet, assumptions of common measures of dependence can fail or estimating such dependence is computationally intensive. This article presents the copula method for modeling the joint distribution of two random variables, including…
Descriptors: Sociology, Research Methodology, Social Science Research, Models
Porter, Kristin E.; Balu, Rekha – MDRC, 2016
Education systems are increasingly creating rich, longitudinal data sets with frequent, and even real-time, data updates of many student measures, including daily attendance, homework submissions, and exam scores. These data sets provide an opportunity for district and school staff members to move beyond an indicators-based approach and instead…
Descriptors: Models, Prediction, Statistical Analysis, Elementary Secondary Education
van der Ark, L. Andries; Bergsma, Wicher P. – Psychometrika, 2010
In contrast to dichotomous item response theory (IRT) models, most well-known polytomous IRT models do not imply stochastic ordering of the latent trait by the total test score (SOL). This has been thought to make the ordering of respondents on the latent trait using the total test score questionable and throws doubt on the justifiability of using…
Descriptors: Scores, Nonparametric Statistics, Item Response Theory, Models
Ho, Andrew Dean – Journal of Educational and Behavioral Statistics, 2009
Problems of scale typically arise when comparing test score trends, gaps, and gap trends across different tests. To overcome some of these difficulties, test score distributions on the same score scale can be represented by nonparametric graphs or statistics that are invariant under monotone scale transformations. This article motivates and then…
Descriptors: Nonparametric Statistics, Comparative Analysis, Trend Analysis, Scores

Fienberg, Stephen E.; Larntz, F. Kinley, Jr. – Psychometrika, 1971
The Lorge-Solomon approach to group problem solving situations and its extensions to trichotomous response situations are examined by use of the maximum likelihood methods. (DG)
Descriptors: Goodness of Fit, Group Behavior, Models, Nonparametric Statistics