American journal of physical anthropology
-
Am. J. Phys. Anthropol. · Mar 2017
Principal component analysis in the evaluation of osteoarthritis.
The purpose of this study is to demonstrate advantages of principal component analysis (PCA) as a standardized procedure in the evaluation of osteoarthritis (OA) in a skeletal series to: (1) compute aggregate scores for joint complexes that accurately capture pathological expression, (2) reveal which variables describe the most sample variation in OA, (3) enable inter- and intra-sample comparison of results, and (4) formulate predictive models from component-based arthritic scores. ⋯ PCA is a simple, non-parametric method of extracting relevant information from complex OA datasets and summarizes variation based on correlated multi-attributes to reveal a simplified structure of OA expression. Multivariate techniques like PCA should be used to describe discrete OA samples, and are useful to compute population-specific representative measurements for idiopathic joint OA in a skeletal sample.