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Download full textRahayu, Sri; Sugiarto, Teguh; Madu, Ludiro; Holiawati; Subagyo, Ahmad – International Journal of Educational Methodology, 2017
This study aims to apply the model principal component analysis to reduce multicollinearity on variable currency exchange rate in eight countries in Asia against US Dollar including the Yen (Japan), Won (South Korea), Dollar (Hong Kong), Yuan (China), Bath (Thailand), Rupiah (Indonesia), Ringgit (Malaysia), Dollar (Singapore). It looks at yield…
Descriptors: Foreign Countries, Factor Analysis, Multiple Regression Analysis, Correlation
Peer reviewedCramer, Elliot M. – Multivariate Behavioral Research, 1974
Descriptors: Correlation, Matrices, Multiple Regression Analysis, Multivariate Analysis
Peer reviewedCramer, Elliot M. – Multivariate Behavioral Research, 1974
Descriptors: Correlation, Matrices, Multiple Regression Analysis, Multivariate Analysis
Peer reviewedBentler, 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
Ping, Chieh-min; Tucker, Ledyard R. – 1976
Prediction for a number of criteria from a set of predictor variables in a system of regression equations is studied with the possibilities of linear transformations applied to both the criterion and predictor variables. Predictive composites representing a battery of predictor variables provide identical estimates of criterion scores as do the…
Descriptors: Correlation, Factor Analysis, Matrices, Multiple Regression Analysis
Williams, John D. – 1976
The use of characteristic coding (dummy coding) is made in showing solutions to four multivariate problems using canonical analysis. The canonical variates can be themselves analyzed by the use of multiple linear regression. When the canonical variates are used as criteria in a multiple linear regression, the R2 values are equal to 0, where 0 is…
Descriptors: Analysis of Variance, Hypothesis Testing, Matrices, Multiple Regression Analysis
