I have data that includes 'cases' and 'controls' and have carried out hierarchical clustering.
I used the
pvclust package in R to bootstrap the results and significant branches are highlighted with red rectangles (based on au>0.95):
What is clear is that no clustering occurs that separates 'cases' and 'controls', and this is in fact what we expected and want to show. We want to show that the measured variable does not distinguish between cases and controls.
itemApartfrom saying visually no clear clusters emerge that distinguishes between cases and controls are there any objective measures that can be used to say no significant clustering occurs between two groups?
- One observation I have here is that the AU values and the BP values are very different, even though both p-values should be interpreted in a similar fashion, am I missing something?
pvclust(bootstrapping) is not the right option here, is there a better way of showing quantifiably that no significant clustering occurs between two groups? Perhaps some kind of supervised clustering (I am not sure what this even means in this context)?