# Experiments with Multiple Outcome Variables

Some experiments have multiple outcome variables and there can be a need to jointly test the significance of all of these. Where the experiment is a Completely Randomized Single Factor Experiment the following can be done:

- Where the questions containing the variables are all categorical, create a Pick Any question containing all of the variables (flattening Pick One - Multi questions if required) and then conduct the test using this new composite question.
- Where the questions containing the variables are all numeric, or, some numeric and some categorical variables, create a Number - Multi question containing all of the variables, converting any categorical variables to binary variables and flattening Pick One - Multi questions if required, and then conduct the test using this new composite question.
- Create a Tree with the outcomes selected as
**Questions to analyze**, the group variable selected as**splitting by questions**and, in**Advanced**, the**Model selection criterion**as**AIC**.