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Drechsler, Jörg – Journal of Educational and Behavioral Statistics, 2015
Multiple imputation is widely accepted as the method of choice to address item-nonresponse in surveys. However, research on imputation strategies for the hierarchical structures that are typically found in the data in educational contexts is still limited. While a multilevel imputation model should be preferred from a theoretical point of view if…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Educational Research, Statistical Bias
Sabitha, Sai; Mehrotra, Deepti; Bansal, Abhay – Interdisciplinary Journal of E-Learning and Learning Objects, 2014
Today Learning Management Systems (LMS) have become an integral part of learning mechanism of both learning institutes and industry. A Learning Object (LO) can be one of the atomic components of LMS. A large amount of research is conducted into identifying benchmarks for creating Learning Objects. Some of the major concerns associated with LO are…
Descriptors: Data Collection, Integrated Learning Systems, Delivery Systems, Mathematics
Karagiannakis, Giannis N.; Baccaglini-Frank, Anna E.; Roussos, Petros – Australian Journal of Learning Difficulties, 2016
Through a review of the literature on mathematical learning disabilities (MLD) and low achievement in mathematics (LA) we have proposed a model classifying mathematical skills involved in learning mathematics into four domains (Core number, Memory, Reasoning, and Visual-spatial). In this paper we present a new experimental computer-based battery…
Descriptors: Mathematics Skills, Mathematical Aptitude, Skill Analysis, Learning Disabilities
Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2007
A common mistake in analysis of cluster randomized trials is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This typically leads to an overstatement of the precision of results and anticonservative conclusions about precision and statistical significance of treatment effects. This…
Descriptors: Statistical Significance, Computation, Cluster Grouping, Statistics
Shafto, Michael – 1972
The purpose of this paper is to suggest a technique of cluster analysis which is similar in aim to the Interactive Intercolumnar Correlation Analysis (IICA), though different in detail. Two methods are proposed for extracting a single bipolar factor (a "contrast compenent") directly from the initial similarities matrix. The advantages of this…
Descriptors: Bibliographies, Classification, Cluster Analysis, Cluster Grouping

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