When fitting hierarchical regression models, maximum likelihood (ML) estimation has computational (and, for some users, philosophical) advantages compared to full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix (S) of group-level varying coefficients are often degenerate. One can do better, even from…

When fitting hierarchical regression models, maximum likelihood (ML) estimation has computational (and, for some users, philosophical) advantages compared to full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix [sigma] of group-level varying coefficients are often degenerate. One can do better, even…

This four-part report discusses the planning of modules through the use of a matrix and contains two case studies as illustration. Part 1, "Applying the Matrix to an Existing Course Outline," shows how to analyze a course outline, adapt it to a matrix, and plan appropriate modules. Part 2, "Matrix Analysis," examines the matrix in order to…

The multivariate general linear hypothesis (MGLH) has received relatively little utilization in educational research and evaluation. This is surprising in view of the fact that recent publications have made the MGLH tractable by practitioners. This paper seeks to stimulate interest in the MGLH by reviewing recent applications, emphasizing the…

Despite advances in common factor analysis, a review of 89 studies published in four selected journals between 1963 and 1976 indicated that behavioral scientists preferred principal components analysis, followed by varimax or orthogonal rotation. Resultant row sums of squares of factor matrices from principal component analyses of real data sets…

This is one of a series of reports on the National Longitudinal Study of Mathematical Abilities (NLSMA). This one is a summary of NLSMA Reports Nos. 21-25, presented as an aid in searching for patterns across various correlates, various mathematical achievement measures, and various samples. In the original analyses, students were grouped into…

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…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…