UPCOMING WEBINAR: From Thousands of Tables To One Clear Story: using AI in survey analysis This article describes how to go from a Principal Component Analysis, Correspondence Analysis, t-SNE or another dimension reduction output:
To a saved component/dimension variable set:
Requirements
- A dimension reduction output created in Displayr, such as Principal Component Analysis, Correspondence Analysis, Multidimensional Scaling, or t-SNE.
Method
1. Select your dimension reduction output.
2. From the Report tree select + > Advanced Analysis > Dimension Reduction > Save Variable(s) > Components/Dimensions.
A new variable set called 'Scores from dim.reduce' will be added to the top of your Report tree, where dim.reduce is the name of the dimension reduction output.
Additional notes
For Principal Component Analysis (PCA), the correlation between these underlying variables and the individual variables used in the analysis is shown in the Rotated Component Matrix. This is typically true, but not always. It can not be the case if there is missing data or if a non-standard method is used to create the saved variables.
Next
How to Do Principal Component Analysis in Displayr
How to Create a Principal Component Analysis Biplot
How to Create a Dimension Reduction Scatterplot
How to Create a Component Plot from a Principal Component Analysis
How to Create a Goodness of Fit Plot from a Dimension Reduction Output
How to Create a Scree Plot from a Principal Component Analysis
How to Do Multidimensional Scaling
How to Create a Distance Matrix