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Frane, James W. – Psychometrika, 1976
Several procedures are outlined for replacing missing values in multivariate analyses by regression values obtained in various ways, and for adjusting coefficients (such as factor score coefficients) when data are missing. None of the procedures are complex or expensive. (Author)
Descriptors: Correlation, Discriminant Analysis, Factor Analysis, Multiple Regression Analysis
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Huberty, Carl J. – Journal of Experimental Education, 1972
It is shown that in the special case of just two criterion groups the predictor variables may be equivalently ordered (with respect to contribution to prediction or discrimination) by the univariate F-ratios and by estimates of the predictor versus the linear discriminant function correlations. (Author)
Descriptors: Behavioral Science Research, Discriminant Analysis, Mathematical Applications, Multiple Regression Analysis
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Roscoe, John T.; Kittleson, Howard M. – Journal of Experimental Education, 1972
Copies of a complete multiple regression computer program (incorporating the modified Gauss-Jordan procedure) and instructions for its use may be found in the senior author's recent book, The Funstat Package in Fortran IV,'' Holt, Rinehart and Winston. (Authors/CB)
Descriptors: Computer Programs, Correlation, Educational Research, Mathematical Applications
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Muhich, Dolores – Educational and Psychological Measurement, 1972
Major objective in this study was the structuring of a predictive model that would assess combinations of variables that most effectively and parsimoniously measure and forecast college success. (Author)
Descriptors: Criteria, Mathematical Models, Multiple Regression Analysis, Predictive Measurement
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Bellante, Donald M. – Journal of Human Resources, 1972
Benefit-cost relationships are estimated for many subgroups of disabled persons. (BH)
Descriptors: Comparative Analysis, Cost Effectiveness, Disabilities, Individual Characteristics
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Leppert, Edward; Hoy, Wayne K. – Journal of Experimental Education, 1972
Results of this study support the view that ideology formation is a function of both personality and social system factors. (Authors/MB)
Descriptors: Discipline, Educational Research, Individual Psychology, Measurement
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Capra, J. R.; Elster, R. S. – Educational and Psychological Measurement, 1971
This method of generating multivariate data differs from previous techniques in that it uses Crout factorization to develop the desired variance-covariance matrix. (Author/CK)
Descriptors: Computer Programs, Mathematical Models, Mathematics, Multiple Regression Analysis
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Schmidt, Frank L. – Educational and Psychological Measurement, 1971
Descriptors: Multiple Regression Analysis, Predictor Variables, Psychology, Raw Scores
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Helsel, A. Ray – Journal of Educational Administration, 1971
Tests hypotheses on educators' orientations toward pupil control. (Author)
Descriptors: Authoritarianism, Educational Research, Humanism, Multiple Regression Analysis
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Rock, Donald A.; And Others – Educational and Psychological Measurement, 1970
Descriptors: Monte Carlo Methods, Multiple Regression Analysis, Predictive Measurement, Predictor Variables
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Woodall, W. Gill; Hill, Susan E. Kogler – Perceptual and Motor Skills, 1982
The relationship between empathy and style of leadership was investigated. Small groups of undergraduates were assessed for predictive and perceived empathy and for leadership style. Multiple regression analysis indicated that predictive, but not perceived, empathy was a significant predictor of leadership style. Other components of leadership…
Descriptors: Empathy, Higher Education, Leadership Qualities, Leadership Styles
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Bentler, P. N.; Freeman, Edward H. – Psychometrika, 1983
Interpretations regarding the effects of exogenous and endogenous variables on endogenous variables in linear structural equation systems depend upon the convergence of a matrix power series. The test for convergence developed by Joreskog and Sorbom is shown to be only sufficient, not necessary and sufficient. (Author/JKS)
Descriptors: Data Analysis, Mathematical Models, Matrices, Multiple Regression Analysis
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Lane, David M. – Multivariate Behavioral Research, 1981
Problems in testing main effects in regression analysis when there is interaction are discussed. A method by which main effects can be tested independently of the interaction is developed and compared with the hierarchical method. The method provides control of the type I error rate, but is quite conservative. (Author/JKS)
Descriptors: Aptitude Treatment Interaction, Data Analysis, Hypothesis Testing, Mathematical Models
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Williams, John T. – Multiple Linear Regression Viewpoints, 1979
A process is described for multiple comparisons when covariates are involved in the analysis. The method can be accomplished with considerable ease whenever pairwise comparisons are involved. More complex contrasts require the use of full and restricted models of variance. (CTM)
Descriptors: Analysis of Covariance, Comparative Analysis, Hypothesis Testing, Multiple Regression Analysis
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Sklar, Michael G. – Journal of Educational Statistics, 1980
It has long been popular to utilize the least squares estimation procedure for fitting the multiple linear regression model to observed data. In this paper, two useful alternatives to least squares estimation in exploratory data analysis are examined: least absolute value estimation and Chebychev estimation. (Author/JKS)
Descriptors: Data Analysis, Least Squares Statistics, Linear Programing, Mathematical Formulas
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