PaleopathV1, Main, Exploration, bibRecord, 000031

Principal component analysis in the evaluation of osteoarthritis.

Identifieur interne : 000031 ( Main/Exploration ); précédent : 000030; suivant : 000032

Principal component analysis in the evaluation of osteoarthritis.

Auteurs : Stephanie E. Calce [Canada] ; Helen K. Kurki [Canada] ; Darlene A. Weston [Canada] ; Lisa Gould [Canada]

Source :

American journal of physical anthropology [ 1096-8644 ] ; 2016.

RBID : pubmed:27896800

Abstract

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.

DOI: 10.1002/ajpa.23130
PubMed: 27896800

Affiliations:

Canada

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<front><div type="abstract" xml:lang="en">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.</div>
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Principal component analysis in the evaluation of osteoarthritis.

Principal component analysis in the evaluation of osteoarthritis.

Source :

Abstract

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Le document en format XML

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