Table 4 Summary of the main steps taken in the PCA-based approach
Main steps of PCA-based analysis | Description | References |
|---|---|---|
Data preparation | Normalization, certifying all variables are within the same range | |
Correlation and suitability to PCA | Determination of the relationship between variables; Bartlett's test of sphericity to certify the correlation matrix is significantly different from identity matrix | |
PCA | Determination of variance captured by each component (eigenvalues), direction of each component (eigenvectors), total variance explained by each component (shared variance) and proportion of each variable's variance explained by component (communalities) | |
Factorial scores | Determination of component scores for each observation, representing their contribution and relative weights in the selected components. These scores integrate the original variables with dimensionality reduction, enabling direct comparison between observations | Alesso et al. 2023 |