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Sudipta Mondal – ProQuest LLC, 2024
Graph neural networks (GNN) are vital for analyzing real-world problems (e.g., network analysis, drug interaction, electronic design automation, e-commerce) that use graph models. However, efficient GNN acceleration faces with multiple challenges related to high and variable sparsity of input feature vectors, power-law degree distribution in the…
Descriptors: Graphs, Models, Computers, Scaling
Lee Wolff; Haydn Till; Bruce Watt – Journal of Psychoeducational Assessment, 2025
Fetal Alcohol Spectrum Disorder (FASD) is a significant public health concern arising from prenatal alcohol exposure. This study examines the clinical utility of Wechsler intelligence tests in assessing cognition in 108 children with confirmed prenatal alcohol exposure. Data were analysed using multidimensional scaling and Guttman's Structural…
Descriptors: Fetal Alcohol Syndrome, Intelligence Tests, Children, Multidimensional Scaling
Jia Liu; Xiangbin Meng; Gongjun Xu; Wei Gao; Ningzhong Shi – Grantee Submission, 2024
In this paper, we develop a mixed stochastic approximation expectation-maximization (MSAEM) algorithm coupled with a Gibbs sampler to compute the marginalized maximum a posteriori estimate (MMAPE) of a confirmatory multidimensional four-parameter normal ogive (M4PNO) model. The proposed MSAEM algorithm not only has the computational advantages of…
Descriptors: Algorithms, Achievement Tests, International Assessment, Foreign Countries
Jia Liu; Xiangbin Meng; Gongjun Xu; Wei Gao; Ningzhong Shi – Journal of Educational Measurement, 2024
In this paper, we develop a mixed stochastic approximation expectation-maximization (MSAEM) algorithm coupled with a Gibbs sampler to compute the marginalized maximum a posteriori estimate (MMAPE) of a confirmatory multidimensional four-parameter normal ogive (M4PNO) model. The proposed MSAEM algorithm not only has the computational advantages of…
Descriptors: Algorithms, Achievement Tests, Foreign Countries, International Assessment
Güler Yavuz Temel – Journal of Educational Measurement, 2024
The purpose of this study was to investigate multidimensional DIF with a simple and nonsimple structure in the context of multidimensional Graded Response Model (MGRM). This study examined and compared the performance of the IRT-LR and Wald test using MML-EM and MHRM estimation approaches with different test factors and test structures in…
Descriptors: Computation, Multidimensional Scaling, Item Response Theory, Models
Ruoxuan Li; Lijuan Wang – Grantee Submission, 2024
Causal-formative indicators are often used in social science research. To achieve identification in causal-formative indicator modeling, constraints need to be applied. A conventional method is to constrain the weight of a formative indicator to be 1. The selection of which indicator to have the fixed weight, however, may influence statistical…
Descriptors: Social Science Research, Causal Models, Formative Evaluation, Measurement
Lisa Chu; Lydia Rainey; Steven Weiner – Center on Reinventing Public Education, 2024
Innovative staffing models are promising, but challenging to scale up. What does the work of leading strategic staffing involve, and what could make scaling up easier? This report digs deep into the many challenges system leaders face when scaling up innovative staffing solutions. These leaders are trying to address longstanding teacher shortages…
Descriptors: Models, Scaling, Personnel Selection, Trust (Psychology)