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Paul A. Jewsbury; Matthew S. Johnson – Large-scale Assessments in Education, 2025
The standard methodology for many large-scale assessments in education involves regressing latent variables on numerous contextual variables to estimate proficiency distributions. To reduce the number of contextual variables used in the regression and improve estimation, we propose and evaluate principal component analysis on the covariance matrix…
Descriptors: Factor Analysis, Matrices, Regression (Statistics), Educational Assessment
Oort, Frans J.; Jak, Suzanne – Research Synthesis Methods, 2016
Meta-analytic structural equation modeling (MASEM) involves fitting models to a common population correlation matrix that is estimated on the basis of correlation coefficients that are reported by a number of independent studies. MASEM typically consist of two stages. The method that has been found to perform best in terms of statistical…
Descriptors: Maximum Likelihood Statistics, Meta Analysis, Structural Equation Models, Correlation
Li, Jianmin; And Others – 1992
This paper discusses the issue of multiple testing and overall Type I error rates in contexts other than multiple comparisons of means. It demonstrates, using a 5 x 5 correlation matrix, the application of 5 recently developed modified Bonferroni procedures developed by the following authors: (1) Y. Hochberg (1988); (2) B. S. Holland and M. D.…
Descriptors: Comparative Analysis, Correlation, Hypothesis Testing, Mathematical Models
Peer reviewedGlorfeld, Louis W. – Educational and Psychological Measurement, 1995
A modification of Horn's parallel analysis is introduced that is based on the Monte Carlo simulation of the null distributions of the eigenvalues generated from a population correlation identity matrix. This modification reduces the tendency of the parallel analysis procedure to overextract or to extract poorly defined factors. (SLD)
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices
Kaplan, David – 1993
The impact of the use of data arising from balanced incomplete block (BIB) spiralled designs on the chi-square goodness-of-fit test in factor analysis is considered. Data from BIB designs posses a unique pattern of missing data that can be characterized as missing completely at random (MCAR). Standard approaches to factor analyzing such data rest…
Descriptors: Chi Square, Computer Simulation, Correlation, Factor Analysis
Thompson, Bruce; Borrello, Gloria M. – 1987
Attitude measures frequently produce distributions of item scores that attenuate interitem correlations and thus also distort findings regarding the factor structure underlying the items. An actual data set involving 260 adult subjects' responses to 55 items on the Love Relationships Scale is employed to illustrate empirical methods for…
Descriptors: Adults, Analysis of Covariance, Attitude Measures, Correlation

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