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Analysis of Multiple Dependent Variables$
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Patrick Dattalo

Print publication date: 2013

Print ISBN-13: 9780199773596

Published to Oxford Scholarship Online: May 2013

DOI: 10.1093/acprof:oso/9780199773596.001.0001

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Multivariate Analysis of Variance

Multivariate Analysis of Variance

Overview and Key Concepts

Chapter:
(p.22) 2 Multivariate Analysis of Variance
Source:
Analysis of Multiple Dependent Variables
Author(s):

Patrick Dattalo

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199773596.003.0002

This chapter presents multivariate analysis of variance (MANOVA) as a generalization of the t-test and analysis of variance (ANOVA). The t-test is a strategy to test hypotheses about differences between two groups on a single mean. When there are more than two means, it is possible to use a series of t-tests to evaluate hypotheses about the difference between each pair of group means (e.g., for three groups, there are three unique pairs of means). However, conducting multiple t-tests can lead to inflation of the type I error rate. Consequently, ANOVA is used to test hypotheses about differences between three or more groups on a single mean; and MANOVA is a strategy to test hypotheses about differences between two or more groups on two or more means (i.e., a vector of means). As a generalization of the t-test and ANOVA, MANOVA may be understood as the ratio between two measures of multivariate variance.

Keywords:   MANOVA, t-test, ANOVA, dependent variables, independent variables, statistical analysis

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