Principal Component Approximation and Interpretation in Health Survey and Biobank Data
Background: Increasing numbers of variables in surveys and administrative databases are created. Principal component analysis (PCA) is important to summarize data or reduce dimensionality. However, one disadvantage of using PCA is the interpretability of the principal components (PCs), especially in...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2018-06-01
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| Series: | Frontiers in Digital Humanities |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fdigh.2018.00011/full |