26th Nov, 2014

University of Birmingham

Question

Asked 13th Nov, 2014

Deleted profile

I am familiar with statistical software (R, GenStat) producing loadings when performing PCA. However, can loadings be extracted from PCoA?

Thanks in advance for any suggestions

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PCoA is applied to a pairwise dissimilarity matrix, which is symmetric. The loadings are therefore equal to the transpose of the scores and not comparable with loadings from standard PCA.

If you are interested in extracting information about variables from PCoA then these articles may be of interest to you:

1) G.J. Postma, P.W.T. Krooshof, L.M.C. Buydens, Analytica Chimica Acta, 705 (2011) 123-134

2) J.C. Gower, S.A. Harding, Biometrika, 75 (1988) 445-455

5 Recommendations

PCoA is applied to a pairwise dissimilarity matrix, which is symmetric. The loadings are therefore equal to the transpose of the scores and not comparable with loadings from standard PCA.

If you are interested in extracting information about variables from PCoA then these articles may be of interest to you:

1) G.J. Postma, P.W.T. Krooshof, L.M.C. Buydens, Analytica Chimica Acta, 705 (2011) 123-134

2) J.C. Gower, S.A. Harding, Biometrika, 75 (1988) 445-455

5 Recommendations

The purposes and methods of PCA are similar but differ slightly. The Eigenvalues are used to identify the components, same as with Factor analysis. But the components aren't typically rotated (you are doing an orthogonal extraction with PCA) and they are like correlations with the individual components. You can translate similarly with >0.4 but they aren't rotated so there isn't separation as with Factor Analysis. You don't usually interpret them but some people use the component scores in furrther analysis.

1 Recommendation

I did a PCA at Melbourne Uni a decade ago with SPSS and the guidebook used came from uni of Wollongong from memory. I just used SPSS help file to learn as I'd never done this before.

PCoA is applied to a pairwise dissimilarity matrix, which is symmetric. The loadings are therefore equal to the transpose of the scores and not comparable with loadings from standard PCA.

If you are interested in extracting information about variables from PCoA then these articles may be of interest to you:

1) G.J. Postma, P.W.T. Krooshof, L.M.C. Buydens, Analytica Chimica Acta, 705 (2011) 123-134

2) J.C. Gower, S.A. Harding, Biometrika, 75 (1988) 445-455

5 Recommendations

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