Introduction
This article describes how to perform a mixed-mode tree analysis in Q. A Mixed-Mode Tree can be created which predicts the Questions to analyze using predictor questions.
Example
The image below shows a tree which predicts main phone company by age, education and gender.
Requirements
- A categorical variable to be used as Target data.
- At least one variable to select as a Predictor variable.
Method
- The first step depends on which version of Q you are using:
- In Displayr, select Anything > Advanced Analysis > Machine Learning > Mixed-Mode Tree.
- In Q Create > Classifier > Mixed-Mode Trees
- Older versions of Q:
- Create and Segments
- Select splitting by questions (tree)
- Select the questions to be used to form the segments in the Questions to analyze dialog box.
- Select the predictor variables:
- Select the variables into the lower box (that is, the box that is below the box for Questions to analyze.
- If necessary, modify the default options. Note that:
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- By default Q will automatically select the number of segments using the Bayesian information criterion. You can alternatively specify a specific number of segments by selecting the Manual option. Alternatively, you can select a different information criteria by clicking Advanced.
- The Question Type of the questions that are analyzed determines how the latent class model is conducted. For example, when analyzing a Pick One - Multi any scale points are ignored and Q treats the data as categorical; if it is converted to a Ranking Q focuses on understanding relativities; if it is converted to Number - Multi Q treats the data as being numeric.
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Next
How to Perform a Mixed-Mode Cluster Analysis