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| Multiple Linear Regression… | 8 |
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| Huitema, Bradley E. | 2 |
| Mouw, John T. | 2 |
| Fraas, John W. | 1 |
| House, Gary D. | 1 |
| Newman, Isadore | 1 |
| Nu, View | 1 |
| Vu, Nu Viet | 1 |
| Williams, John T. | 1 |
| Wolfle, Lee M. | 1 |
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| Journal Articles | 3 |
| Reports - Research | 3 |
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Peer reviewedWilliams, 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
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 reviewedHuitema, Bradley E. – Multiple Linear Regression Viewpoints, 1978
Issues in analysis of covariance, multiple regression analysis, and the analysis of variance such as the assumption of independence and directional hypotheses are discussed. (JKS)
Descriptors: Analysis of Covariance, Analysis of Variance, Data Analysis, Multiple Regression Analysis
Peer reviewedMouw, John T.; Nu, View – Multiple Linear Regression Viewpoints, 1979
Repeated measures designs often involve dichotomization of a continuous variable in order to be amenable to the analysis of variance nature of such designs. An alternative to that approach wherein the independent variable is kept continuous is presented. (JKS)
Descriptors: Analysis of Covariance, Analysis of Variance, Hypothesis Testing, Multiple Regression Analysis
Peer reviewedMouw, John T.; Vu, Nu Viet – Multiple Linear Regression Viewpoints, 1979
Repeated measures designs often involve dichotomization of a continuous variable in order to be amenable to the analysis of variance nature of such designs. An alternative to that approach wherein the independent variable is kept continuous is presented. (JKS)
Descriptors: Analysis of Covariance, Analysis of Variance, Hypothesis Testing, Multiple Regression Analysis
Peer reviewedFraas, 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
Peer reviewedHouse, Gary D. – Multiple Linear Regression Viewpoints, 1978
The three-year impact of a remedial arithmetic program on eligible St. Louis Public School pupils was investigated. Hypotheses were tested through multiple linear regression models for analyses of covariance. No treatment effects were found. The study reveals that changes in future program evaluation designs are needed. (Author/JKS)
Descriptors: Academic Achievement, Analysis of Covariance, Arithmetic, Intermediate Grades
