Hi Tania,
Even though there is no perfect answer: don't use the combination Hellinger
transformation + Bray-Curtis distance. The appropriate combination is Hellinger
transformation + Euclidean distance, which gives you Hellinger distances (this
is an asymmetric dissimilarity measure, which does
Hi Tania,
That's not really an R question, and there's no one perfect answer.
Googling "distance metric for ordinal data" turns up some discussions of
the pros and cons of the various options.
You need to choose the one best able to address your hypothesis. You might
get better ideas on a statist
Dear all,
I have the following experimental design: 9 mice (mouseID) were assigned to
three different treatments (3 mice per treatment level) and we estimated
the composition of microbial species in the gut at 5 time points (same time
points for each mouse). I would like to know if the community d
I have species data that I would like to use for ordination. With
regular abundance data I would apply a Hellinger Transformation and
then use the Bray-Curtis distance.
Since the data are ranked (0 to 5) I will not transform it. But what
dissimilarity measure should I use instead of Bray-Curtis?
