## Multivariate Analysis of Variance, Issue 54Bray's monograph considers the multivariate form of analysis of variance (MANOVA). The primary emphasis of the book is on methods for interpreting MANOVA statistical analyses. These are illustrated through the use of two numerical examples: one involves a small, hypothetical data set, which can be analyzed by the reader with minimal effort; the other involves real data and shows how MANOVA can be used in actual research. MANOVA represents a logical extension of |

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### Contents

5 | |

Omnibus MANOVA Tests | 13 |

Analyzing and 1nterpreting Significant MANOVAs | 39 |

Causal Models Underlying MANOVA Analyses | 57 |

75 | |

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### Common terms and phrases

alpha level analysis of variance assumptions between-group Bock Bonferroni canonical correlations canonical variate correlations centroids classification variables complex conceptual considered contrasts covariance criterion variables CVCs degrees of freedom dependent variables discriminant analysis discriminant coefficients discriminant function discriminant space discriminant variates discussed effects eigenvalues equal experimentwise error rate F distribution F test F-to-remove factor Figure 2.2a follow-up full model group centroids group differences group means group separation Huberty hypothetical data important for group k groups lambda linear combination matrix method multiple multivariate analysis multivariate null hypothesis multivariate test nominal alpha Olson omnibus test overall MANOVA test path Pillai-Bartlett trace population mean PPVT procedure readers reduced model regression represent researcher robust to violations sample sizes score SDWs Section separate ANOVAs significant MANOVA statistical power statistically significant step-down Stevens sum of squares Tatsuoka techniques tion Type 1 error univariate ANOVA univariate F ratios univariate tests variables simultaneously vectors Wilks within-group