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Weinberg, Sharon L.; Darlington, Richard B. – Journal of Educational Statistics, 1976
Problems of sampling error and accumulated rounding error in canonical variate analysis are discussed. A new technique is presented which appears to be superior to canonical variate analysis when the ratio of variables to sampling units is greater than one to ten. Examples are presented. (Author/JKS)
Descriptors: Correlation, Matrices, Multivariate Analysis, Sampling

Reddon, John R. – Journal of Educational Statistics, 1987
Computer sampling from a multivariate normal spherical population was used to evaluate Type I error rates for a test of P = I based on Fisher's tanh(sup minus 1) variance stabilizing transformation of the correlation coefficient. (Author/TJH)
Descriptors: Computer Simulation, Correlation, Monte Carlo Methods, Multivariate Analysis

Rosenbaum, Paul R. – Journal of Educational Statistics, 1986
Using data from the High School and Beyond, this article presents statistical procedures to estimate the effect of dropping out of high school on cognitive achievement test scores. Each sampled dropout is matched to a student remaining in the same school. Methods for addressing the possible omission of covariates are described. (BS)
Descriptors: Achievement Tests, Analysis of Covariance, Dropouts, Effect Size

Raudenbush, Stephen W.; And Others – Journal of Educational Statistics, 1991
A three-level multivariate statistical modeling strategy is presented that resolves the question of whether the unit of analysis should be the teacher or the student. A reanalysis of U.S. high school data (51 Catholic and 59 public schools from the High School and Beyond survey) illustrates the model. (SLD)
Descriptors: Algorithms, Catholic Schools, Educational Environment, Equations (Mathematics)