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| Journal of Educational… | 10 |
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| Journal Articles | 10 |
| Reports - Evaluative | 6 |
| Reports - Research | 4 |
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Peer reviewedLutz, J. Gary; Cundari, Leigh A. – Journal of Educational Statistics, 1989
Means of identifying sources of rejection of hypotheses regarding linear multivariate statistical models are discussed. Problems with the use of a global test using Roy's largest root criterion and means of solving them are presented, along with a practical application of the techniques. (TJH)
Descriptors: Hypothesis Testing, Mathematical Formulas, Mathematical Models, Multivariate Analysis
Peer reviewedSzatrowski, Ted – Journal of Educational Statistics, 1982
Known results for testing and estimation problems for patterned means and covariance matrices with explicit linear maximum likelihood estimates are applied to the block compound symmetry problem. An example involving educational testing is provided. (Author/JKS)
Descriptors: Hypothesis Testing, Mathematical Models, Maximum Likelihood Statistics, Multivariate Analysis
Peer reviewedHuberty, Carl J.; Wisenbaker, Joseph M. – Journal of Educational Statistics, 1992
Interpretations of relative variable importance in multivariate analysis of variance are discussed, with attention to (1) latent construct definition; (2) linear discriminant function scores; and (3) grouping variable effects. Two numerical ranking methods are proposed and compared by the bootstrap approach using two real data sets. (SLD)
Descriptors: Analysis of Variance, Comparative Analysis, Equations (Mathematics), Mathematical Models
Peer reviewedJoe, George W.; Mendoza, Jorge L. – Journal of Educational Statistics, 1989
A response to comments on internal correlation for statistical analysis, as proposed by the present authors (1989), is provided. Focus is on issues raised by W. W. Rozeboom (1989). Comments by J. H. Schuenemeyer (1989) and R. Bargmann (1989) are briefly considered. (TJH)
Descriptors: Correlation, Factor Analysis, Generalization, Mathematical Models
Peer reviewedJoe, George W.; Mendoza, Jorge L. – Journal of Educational Statistics, 1989
The internal correlation--a measure of dependency in a set of variables--is discussed and generalized. Applications of the internal correlation coefficient and its generalizations are given for several data-analytic situations. The internal correlation is illustrated and the concept is expanded to a series of additional indices. (TJH)
Descriptors: Correlation, Equations (Mathematics), Factor Analysis, Generalization
Peer reviewedRozeboom, William W. – Journal of Educational Statistics, 1989
Use of internal correlation for statistical analysis--proposed by G. W. Joe and J. L. Mendoza (1989)--is discussed. Focus is on the "content" question (what this application can do with the information that statistics contain) and the "eloquence" question (the advantages of this means of encoding information over other means). (TJH)
Descriptors: Correlation, Equations (Mathematics), Factor Analysis, Generalization
Peer reviewedRubin, Donald B.; And Others – Journal of Educational Statistics, 1981
A time-saving and space-saving algorithm is presented for computing the sums of squares and estimated cell means under the additive model in a two-way analysis of variance or covariance with unequal numbers of observations in the cells. The procedure is illustrated. (Author/JKS)
Descriptors: Algorithms, Analysis of Covariance, Analysis of Variance, Computer Programs
Peer reviewedAlgina, James; And Others – Journal of Educational Statistics, 1991
Type I error rates for Yao's, James' first-order and second-order, and Johansen's tests of equality of mean vectors for two independent samples were estimated for various conditions defined by the degree of heteroscedasticity and nonnormality. Each procedure can be seriously nonrobust with exponential and log-normal distributions. (TJH)
Descriptors: Analysis of Covariance, Analysis of Variance, Comparative Analysis, Equated Scores
Peer reviewedLongford, Nicholas T. – Journal of Educational Statistics, 1990
A multilevel variance component analysis from the pilot year of pretesting an instrument--the GENED--designed to present information about general education outcomes is presented, using data from about 11,000 college students. The analysis addresses the discriminant validity of the subtests and statistical issues in test construction. (SLD)
Descriptors: College Students, Discriminant Analysis, General Education, Higher Education
Peer reviewedRaudenbush, 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)


