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.