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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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Newman, Isadore; Fraas, John – Multiple Linear Regression Viewpoints, 1979
Issues in the application of multiple regression analysis as a data analytic tool are discussed at some length. Included are discussions on component regression, factor regression, ridge regression, and systems of equations. (JKS)
Descriptors: Correlation, Factor Analysis, Multiple Regression Analysis, Research Design
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Bollen, Kenneth A.; Ward, Sally – Sociological Methods and Research, 1979
Three different uses of ratio variables in aggregate data analysis are discussed: (1) as measures of theoretical concepts, (2) as a means to control an extraneous factor, and (3) as a correction for heteroscedasticity. Alternatives to ratios for each of these cases are discussed and evaluated. (Author/JKS)
Descriptors: Correlation, Multiple Regression Analysis, Predictor Variables, Ratios (Mathematics)
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Messmer, Donald J.; Solomon, Robert J. – Educational and Psychological Measurement, 1979
A method for testing differential predictability in a selection model was illustrated on data from 103 male and 24 female graduate students. Since the models were not homogeneous in the variance, a method for adjusting for heterogeneity was presented. (Author/CTM)
Descriptors: Admission Criteria, Graduate Students, Higher Education, Mathematical Models
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Bridges, Edwin M. – Educational Administration Quarterly, 1980
Although the relationship between teacher job satisfaction and absenteeism is tenuous, the relationship is apt to be stronger under conditions of high work interdependence rather than under moderate or low interdependence. (Author/IRT)
Descriptors: Elementary Education, Job Satisfaction, Multiple Regression Analysis, Teacher Attendance
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Glass, Gene V. – Educational Researcher, 1979
Most of the variance in educational effectiveness studies is inexplicable in terms of influences that can be measured and controlled. Nevertheless, it is still possible to design educational policy that will function well under conditions of uncertainty. (Author/RLV)
Descriptors: Comparative Analysis, Educational Policy, Educational Research, Multiple Regression Analysis
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Cramer, Elliot M.; Appelbaum, Mark I. – Review of Educational Research, 1978
Assuming conditional normality and independence, standard estimation and hypothesis testing procedures for regression coefficients are the same whether using fixed x values, random x values or mixed fixed and random values. Contrary to Sockloff's suggestion, polynomial regression is useful with either fixed or random models. (See EJ 142 050). (CP)
Descriptors: Error of Measurement, Mathematical Models, Multiple Regression Analysis, Research Reviews (Publications)
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Williams, John D. – Multiple Linear Regression Viewpoints, 1979
Some of the more simplified methods for contrasts with equal sample sizes in multiple regression analysis are shown to result in erroneous calculations when applied to data sets with unequal sample sizes. An alternative method is provided. (Author/JKS)
Descriptors: Analysis of Variance, Hypothesis Testing, Multiple Regression Analysis, Research Methodology
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Morris, John D. – Educational and Psychological Measurement, 1979
Several advantages to the use of different kinds of factor scores as independent variables in a multiple regression equation are reported. A computer program is presented which will calculate a regression equation using a variety of factor scores. (Author/JKS)
Descriptors: Computer Programs, Factor Analysis, Multiple Regression Analysis, Program Descriptions
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Smith, Kent W.; Sasaki, M. S. – Sociological Methods and Research, 1979
A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)
Descriptors: Correlation, Hypothesis Testing, Mathematical Models, Multiple Regression Analysis
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Gustafson, Charles R.; Michael, Joan J. – Educational and Psychological Measurement, 1976
Grade point average for a sample of graduate school of education students was more accurately predicted from undergraduate grade point average than from part of total scores on the Undergraduate Record Examination. However, the Advance Education examination of the Undergraduate Record Examination did improve the prediction equation. (Author/JKS)
Descriptors: College Entrance Examinations, Grades (Scholastic), Graduate Students, Multiple Regression Analysis
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