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A Multivariate Analysis of Variance of Categorical Data
Biometrical Journal, 1986AbstractTwo methods of testing multivariate hypotheses in an IXJXK contingency table are presented. In one case, use is made of the trace of the matrix of sum of squares and sum of products while in the other, determinants of the matrices are used to construct test statistics. Asymptotic equivalence of the methods is shown.
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Multivariate Analysis of Variance
This chapter examines the analysis of variance (ANOVA) and Fisher statistical tests as fundamental research methods. Introduction to ANOVA and its application to the investigation of significant differences between data groups. Subsequently, we examine the application of Fisher tests in various contexts, including one-factor, two-factor, and even three-openaire +1 more source
Multivariate Analysis of Variance
1988More than two decades have passed since Lyle Jones (1966) wrote a chapter titled “Analysis of Variance in Its Multivariate Developments” in the first edition of this handbook. Many new developments have been made, and the technique has come to be much more widely known and applied in the behavioral sciences. The term “multivariate analysis of variance”
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Multivariate Analysis of Variance
1998The multivariate analysis of variance (MANOVA) is a generalization of analysis of variance when there are multiple dependent variables, and tests whether mean differences among groups on a combination of dependent variables is a chance occurrence. A new dependent variable that maximizes group differences is created from the set of dependent variables ...
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Academic Emergency Medicine, 1998
ABSTRACTMedical research frequently involves the statistical comparison of >2 groups, often using data obtained through the application of complex experimental designs. Fortunately, inferential statistical methodologies exist to address these situations.
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ABSTRACTMedical research frequently involves the statistical comparison of >2 groups, often using data obtained through the application of complex experimental designs. Fortunately, inferential statistical methodologies exist to address these situations.
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