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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
James Ohisei Uanhoro – Structural Equation Modeling: A Multidisciplinary Journal, 2024
We present a method for Bayesian structural equation modeling of sample correlation matrices as correlation structures. The method transforms the sample correlation matrix to an unbounded vector using the matrix logarithm function. Bayesian inference about the unbounded vector is performed assuming a multivariate-normal likelihood, with a mean…
Descriptors: Bayesian Statistics, Structural Equation Models, Correlation, Monte Carlo Methods
Alexander von Eye; Wolfgang Wiedermann – Merrill-Palmer Quarterly: A Peer Relations Journal, 2024
In this article, we pursue two points of discussion. First, a new illustration is presented of the person-oriented tenet according to which it can be hazardous to generalize to the individual results that are based on the analysis of aggregated data. Second, it is illustrated that taking into account serial dependence information can result in not…
Descriptors: Research Methodology, Generalizability Theory, Generalization, Multivariate Analysis
Rozenszajn, Ronit; Kavod, Galia Zer; Machluf, Yossy – International Journal of Science Education, 2021
The Repertory Grid Technique (RGT) is a qualitative method, based on the Personal Construct Psychology (PCP) theory, which provides a powerful tool to elicit tacit personal construction systems, with minimal intervention and interpretation. Although the contributory potential of the RGT as a cognitive research tool in science education has been…
Descriptors: Cognitive Structures, Psychology, Theories, Science Education
Newman, David; Newman, Isadore; Ridenour, Carolyn; Morales, Jennifer – Journal of Research in Education, 2014
The authors describe five value-added methods (VAM) used in school assessment as the backdrop to their main thesis. Then they review the assumptions underlying measurement and evaluation, the foundation of all assessment systems, including value-added. They discuss the traditional criterion variable used in VAM: a standardized test score. Next,…
Descriptors: Value Added Models, Educational Assessment, Standardized Tests, Scores
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
Chiu, Chia-Yi; Köhn, Hans-Friedrich; Wu, Huey-Min – International Journal of Testing, 2016
The Reduced Reparameterized Unified Model (Reduced RUM) is a diagnostic classification model for educational assessment that has received considerable attention among psychometricians. However, the computational options for researchers and practitioners who wish to use the Reduced RUM in their work, but do not feel comfortable writing their own…
Descriptors: Educational Diagnosis, Classification, Models, Educational Assessment
Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman – Psychological Methods, 2013
In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree…
Descriptors: Structural Equation Models, Multivariate Analysis, Computation, Factor Analysis
Sorensen-Unruh, Clarissa – Journal of Chemical Education, 2017
This Communication summarizes one of the invited papers to the Select 2016 BCCE Presentations ACS CHED Committee on Computers in Chemical Education online ConfChem held from October 30 to November 22, 2016. The ConfChem paper (included within Supporting Information) focuses on the results of one instructor's incorporation of social media into her…
Descriptors: Chemistry, Computer Uses in Education, Conferences (Gatherings), Teaching Methods
Svetina, Dubravka; Levy, Roy – Applied Psychological Measurement, 2012
An overview of popular software packages for conducting dimensionality assessment in multidimensional models is presented. Specifically, five popular software packages are described in terms of their capabilities to conduct dimensionality assessment with respect to the nature of analysis (exploratory or confirmatory), types of data (dichotomous,…
Descriptors: Computer Software, Item Response Theory, Models, Factor Analysis
Cheung, Mike
W.-L. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Structural equation modeling (SEM) is now a generic modeling framework for many multivariate techniques applied in the social and behavioral sciences. Many statistical models can be considered either as special cases of SEM or as part of the latent variable modeling framework. One popular extension is the use of SEM to conduct linear mixed-effects…
Descriptors: Structural Equation Models, Maximum Likelihood Statistics, Guidelines, Multivariate Analysis
Schepers, Jan; Van Mechelen, Iven – Psychological Methods, 2011
Profile data abound in a broad range of research settings. Often it is of considerable theoretical importance to address specific structural questions with regard to the major pattern as included in such data. A key challenge in this regard pertains to identifying which type of interaction (double ordinal, mixed ordinal/disordinal, double…
Descriptors: Matrices, Profiles, Multivariate Analysis, Models
van Smeden, Maarten; Hessen, David J. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
In this article, a 2-way multigroup common factor model (MG-CFM) is presented. The MG-CFM can be used to estimate interaction effects between 2 grouping variables on 1 or more hypothesized latent variables. For testing the significance of such interactions, a likelihood ratio test is presented. In a simulation study, the robustness of the…
Descriptors: Multivariate Analysis, Robustness (Statistics), Sample Size, Statistical Analysis
Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S. – Journal of Nutrition Education and Behavior, 2012
Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…
Descriptors: Nutrition, Statistical Analysis, Sampling, Research
Bergman, Lars R.; Nurmi, Jari-Erik; von Eye, Alexander A. – International Journal of Behavioral Development, 2012
I-states-as-objects-analysis (ISOA) is a person-oriented methodology for studying short-term developmental stability and change in patterns of variable values. ISOA is based on longitudinal data with the same set of variables measured at all measurement occasions. A key concept is the "i-state," defined as a person's pattern of variable…
Descriptors: Classification, Statistical Analysis, Structural Equation Models, Sample Size