I used MANOVA (Multivariate Analysis of Variance) for a quantitative data analysis of my dissertation.
So, when to use MANOVA?
- When you have several dependent variables (DV)
- When there is only one independent variable or when there are several, we can look at interactions between independent variables, and we can even do contrasts to see which groups differ from each other.
What are benefits of using MANOVA?
- we can look at interactions between independent variables
- we can even do contrasts to see which groups differ from each other
- MANOVA can tell us the relationship between DV(outcome variables).
Compared to ANOVA, what are good things of using MANOVA? why MANOVA is used instead of multiple ANOVAs?
- the more tests we conduct on the same data, the more we inflate the familywise error rate; the more dependent variables that have been measured, the more ANOVAs would need to be conducted and the greater the chance of making a Type I error.
- MANOVA has greater power to detect an effect, because it can detect whether groups differ along a combination of variables, whereas ANOVA can detect only if groups differ along a single variable
- ANOVA can tell us only whether groups differ along a single dimension whereas MANOVA has the power to detect whether groups differ along a combination of dimensions.