Multivariate Analysis of Variance (MANOVA)
ANOVA (analysis of variance) tests whether mean differences among groups on a single DV (dependent variable) are likely to have occurred by chance. MANOVA (multivariate analysis of variance) tests whether mean differences among groups on a combinationof DVs are likely to have occurred by chance. For example, suppose a researcher is interested in the effect of different types of treatment (the IV; say, desensitization, relaxation training, and a waiting-list control) on anxiety. In ANOVA, the researcher chooses one measure of anxiety from among many. With MANOVA, the researcher can assess several types of anxiety (say, test anxiety, anxiety in reaction to minor life stresses, and so-called free-floating anxiety). After random assignment of participants to one of the three treatments and a subsequent period of treatment, participants are measured for test anxiety, stress anxiety, and free-floating anxiety. Scores on all three measures for each participant serve as DVs. MANOVA is used...
References and Further Reading
- Bock RD, Haggard EA (1968) The use of multivariate analysis of variance in behavioral research. McGraw-Hill, New YorkGoogle Scholar
- Maxwell S (2001) When to use MANOVA and significant MANOVAs and insignificant ANOVAs or vice versa. J Consum Psychol 10(1–2):29–30Google Scholar
- Tabachnick BG, Fidell LS (2007) Using multivariate statistics. Allyn & Bacon, BostonGoogle Scholar
- Woodward JA, Overall JE (1975) Multivariate analysis of variance by multiple regression methods. Psychol Bull 82(1):21–32Google Scholar