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Healy, J. D. – Psychometrika, 1979
The hypothesis that two variables have a perfect disattenuated correlation and hence measure the same trait, except for errors of measurement, is discussed. Equivalently, the underlying variables, the true scores, are related linearly. It is shown that previously proposed ad hoc tests are, in fact, likelihood ratio tests. (Author/JKS)
Descriptors: Analysis of Covariance, Correlation, Hypothesis Testing, Multiple Regression Analysis
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McDonald, Roderick P. – Psychometrika, 1978
The relationship between the factor structure of a convariance matrix and the factor structure of a partial convariance matrix when one or more variables are partialled out of the original matrix is given in this brief note. (JKS)
Descriptors: Analysis of Covariance, Correlation, Factor Analysis, Factor Structure
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And Others; Werts, Charles E. – Educational and Psychological Measurement, 1979
It is shown how partial covariance, part and partial correlation, and regression weights can be estimated and tested for significance by means of a factor analytic model. Comparable partial covariance, correlations, and regression weights have identical significance tests. (Author)
Descriptors: Analysis of Covariance, Correlation, Factor Analysis, Maximum Likelihood Statistics
Borich, Gary D. – 1971
Methods exist for testing the homogeneity of group regression for the case in which there is only one predictor. Studies which have investigated aptitude-treatment interactions have adopted the homogeneity of regressions test as standard methodology for assessing the difference in regression slopes across treatments. Additional statistical…
Descriptors: Analysis of Covariance, Correlation, Interaction, Interaction Process Analysis
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Fraas, John W.; Newman, Isadore – Multiple Linear Regression Viewpoints, 1978
Problems associated with the use of gain scores, analysis of covariance, multicollinearity, part and partial correlation, and the lack of rectilinearity in regression are discussed. Particular attention is paid to the misuse of statistical techniques. (JKS)
Descriptors: Achievement Gains, Analysis of Covariance, Correlation, Data Analysis
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Bentler, P. M.; Lee, Sik-Yum – Journal of Educational Statistics, 1983
A method for the estimation of covariance structure models under polynomial constraints (such as quadratic constraints) is presented. Estimation is on maximum likelihood principles, and the test statistics, parameter estimates, and standard errors are based on a statistical theory which takes the constraints into account. (Author/JKS)
Descriptors: Analysis of Covariance, Correlation, Estimation (Mathematics), Factor Analysis
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Lee, S. Y.; Jennrich, R. I. – Psychometrika, 1979
A variety of algorithms for analyzing covariance structures are considered. Additionally, two methods of estimation, maximum likelihood, and weighted least squares are considered. Comparisons are made between these algorithms and factor analysis. (Author/JKS)
Descriptors: Analysis of Covariance, Comparative Analysis, Correlation, Factor Analysis
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Walberg, Herbert J. – American Educational Research Journal, 1971
Similarities between regression analysis and analysis of variance are noted and it is argued that the former has advantages over the latter. It is also argued that canonical correlation analysis is more suitable than factor analysis in certain cases. The argument is illustrated with four recent pieces of educational research. (DG)
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Factor Analysis
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Joreskog, Karl G. – Psychometrika, 1978
A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…
Descriptors: Analysis of Covariance, Correlation, Critical Path Method, Factor Analysis
Knapp, Thomas R.; Schafer, William D. – 1971
Two theorems concerning F in analysis of covariance with two groups (experimental and control) and one covariable (pretest score) are presented. The first shows explicitly that F is a direct function of the ratio of the variance about the regression line for the total sample to the variance about the within-group regression line. The second…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Multiple Regression Analysis
Mason, Robert L.; McNeil, Keith A. – 1974
This regression system is an intermediate result of a project to develop a comprehensive regression computer system as a foundation for a complete statistical man-machine interface. The outstanding features of the system can be condensed into two principal concepts. First, the program dynamically allocates core resulting in no limits on title…
Descriptors: Analysis of Covariance, Computational Linguistics, Computer Programs, Correlation
Porter, Andrew C. – 1971
In this paper problems caused by the existence of errors of measurement are identified for factor analysis, regression analysis, ANOVA, and ANCOVA. At least one detrimental effect is shown to exist for each type of analysis. When a researcher's interest is with infallible variables, he runs the risk of biased results from all of the procedures…
Descriptors: Analysis of Covariance, Analysis of Variance, Correlation, Error of Measurement
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Werts, Charles E.; Linn, Robert L. – Educational and Psychological Measurement, 1971
Descriptors: Analysis of Covariance, Correlation, Educational Environment, Error of Measurement
Gray, William M.; Hofmann, Richard J. – 1969
Most responses to educational and psychological test items may be represented in binary form. However, such dichotomously scored items present special problems when an analysis of correlational interrelationships among the items is attempted. Two general methods of analyzing binary data are proposed by Horst to partial out the effects of…
Descriptors: Algorithms, Analysis of Covariance, Cluster Analysis, Cluster Grouping
Cherukupalle, Nirmala devi – 1970
This bibliography contains works that illustrate and apply multivariate statistical methods in the analysis of empirical data in the field of urban and regional planning. The bibliography has been designed for use by planning students and the professional planner. The first section of the bibliography lists some elementary and intermediate level…
Descriptors: Analysis of Covariance, Analysis of Variance, Annotated Bibliographies, Bibliographies
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