Which test is used to investigate more than one dependent variable?

The choice of MANOVA (Multivariate Analysis of Variance) is appropriate because it is specifically designed to examine the differences in multiple dependent variables across one or more independent groups. While ANOVA looks at multiple groups for a single dependent variable, MANOVA extends this concept by allowing researchers to consider multiple dependent variables simultaneously. This is particularly useful when the dependent variables may be correlated, as MANOVA can help to identify patterns and relationships that might not be evident when conducting separate ANOVAs for each dependent variable.

Using MANOVA, researchers can determine if the combined dependent variables differ significantly across the levels of the independent variable, thus providing a more comprehensive view of the data. This holistic approach is why MANOVA is favored for studies involving multiple dependent measures.