What do you need for a MANOVA?
In order to use MANOVA the following assumptions must be met:
- Observations are randomly and independently sampled from the population.
- Each dependent variable has an interval measurement.
- Dependent variables are multivariate normally distributed within each group of the independent variables (which are categorical)
Why do a MANOVA?
The one-way multivariate analysis of variance (one-way MANOVA) is used to determine whether there are any differences between independent groups on more than one continuous dependent variable. In this regard, it differs from a one-way ANOVA, which only measures one dependent variable.
Which is the best method to fit MANOVA?
In your preferred statistical software, fit the MANOVA model so that Method is the independent variable and Satisfaction and Test are the dependent variables. The MANOVA results are below.
Can a MANOVA be performed with more than one response variable?
In this case, we have one explanatory variable and one response variable. A MANOVA is an extension of the one-way ANOVA in which there is more than one response variable. For example, we might be interested in understanding whether or not level of education leads to different annual incomes and different amounts of student loan debt.
Do you need a larger sample size for MANOVA?
Although the larger your sample size, the better; for MANOVA, you need to have more cases in each group than the number of dependent variables you are analysing. Assumption #5: There are no univariate or multivariate outliers.
Which is the first result of a two way MANOVA?
The first result that needs to be interpreted in the two-way MANOVA is the interaction term (i.e., Gender*Intervention), which is found in the Multivariate Tests table, as shown below: Published with written permission from SPSS Statistics, IBM Corporation.