Question: Is it correct to use HCPC analysis (FactoMineR package) on categorical data

Dear Adrian,

Your approach seems correct to me. Your disease severity variable is not categorical but ordinal (semi-quantitative) and you can perform PCA (on the covariance matrix: scale.unit = FALSE) and HCPC on the mean scores as suggested. You can also directly perform a hierarchical clustering of the 109 isolates by applying hclust() to the Euclidean distance matrix.

Best wishes,

Fran?ois

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----- Mail original -----
De: "Adnan Sisic" <adnan_sisic at live.com>
?: "R-sig-ecology at r-project.org" <r-sig-ecology at r-project.org>
Envoy?: Vendredi 15 Juillet 2022 12:32:40
Objet: [R-sig-eco] Question: Is it correct to use HCPC analysis (FactoMineR package) on categorical data

Dear Sig. Ecology members,

I have categorical disease severity data, disease scale - scores from 1 (healthy plant) to 10 (heavily diseased/dying plant). In total  I have 109 isolates tested, each in 3 replicates. Is it correct to use mean score of 3 replicates for each isolate as inputs, calculate Euclidean distances between isolates and perform Hierarchical Clustering on Principal Components (HCPC) in FactoMineR package?

Thanks and best regards,



----

FG ?kologischer Pflanzenschutz
Universit?t Kassel
Nordbahnhofstr. 1a
D-37213 Witzenhausen
Deutschland

Dept. of Ecological Plant Protection
University of Kassel
Nordbahnhofstr. 1a
D-37213 Witzenhausen
Germany

Tel. 05542 98 1569
Fax. 05542 98 1564

www.uni-kassel.de/go/fb11-oekologischer-pflanzenschutz<http://www.uni-kassel.de/go/fb11-oekologischer-pflanzenschutz>

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