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Peer reviewedHuitema, Bradley E. – Multiple Linear Regression Viewpoints, 1978
Many methodologists are aware that parametric tests associated with the analysis of variance and the analysis of covariance can be computed using regression procedures. It is shown that multiple linear regression can also be employed to compute the Kruskal-Wallis nonparametric analysis of variance. (Author)
Descriptors: Analysis of Covariance, Analysis of Variance, Data Analysis, Multiple Regression Analysis
Peer reviewedWolfle, Lee M. – Multiple Linear Regression Viewpoints, 1978
The author is generally critical of the previous article (TM 503 686), which concerned the use of multiple regression for nonparametric analysis of variance. (JKS)
Descriptors: Analysis of Covariance, Analysis of Variance, Data Analysis, Multiple Regression Analysis
Peer reviewedLeitner, Dennis W. – Multiple Linear Regression Viewpoints, 1979
This paper relates common statistics from contingency table analysis to the more familiar R squared terminology in order to better understand the strength of the relation implied. The method of coding contingency tables was shown, as well as how R squared related to phi, V, and chi squared. (Author/CTM)
Descriptors: Correlation, Expectancy Tables, Hypothesis Testing, Multiple Regression Analysis
