Principal Component Analysis
- Metric: standardized (correlations), or identity (covariances).
- Computation of missing data.
- Means or individual scores taken in account. Additional individuals.
- Detailed result edition.
- Correlation circles.
- Planes of the individuals and/or the means.
- BiPlot.
- Analyses may be done also by judge and by descriptor (consistency of the judges).
- Horizontal analyses allow individualizing the attributes by judge. The variables are the Judge - Attribute pairs. Different weighting can be applied to the judges (MFA, STATIS ...).
Example of a BiPlot from Principal Component Analysis:
Optionally you may also project the individual judge scores, which was done in the example shown here (empty symbols). The points with the same given color represent the varied scores for a given product:
