[R] how to combine uncertainty and weighting in spearman correlation?

Abby Spurdle @purd|e@@ @end|ng |rom gm@||@com
Mon Jun 22 00:07:36 CEST 2020


Just realised the above notation may be a bit misleading.
Because I was thinking in terms of simulated data.


On Mon, Jun 22, 2020 at 10:00 AM Abby Spurdle <spurdle.a using gmail.com> wrote:
>
> Hi Frederick,
>
> I glanced at the webpage you've linked.
> (But only the top three snippets).
>
> This is what I would call the sum of random variables.
> (X, Y) = (X1, X1) + (X2, Y2) + ... + (Xn, Yn)
>
> The example makes the mistake of assuming that the Xs are normally
> distributed, and each of the Ys are from exactly the same uniform
> distribution.
> By "combine"-ing both approaches, are you wanting to weight each pair?
>
> w1(X1, X1) + w2(X2, Y2) + ... + wn(Xn, Yn)
>
> I note that you haven't told us much about your data.
> There may be an easier way of doing things...
>
>
> On Mon, Jun 22, 2020 at 1:53 AM Frederik Feys <frefeys using gmail.com> wrote:
> >
> > Hello everyone
> >
> > At the moment I put a lot of attention in the uncertainty of my analyzes. I want to do a spearman correlation that takes into account the uncertainty in my observations and has weighting.
> >
> > uncertainty of observations: I came across this excellent blog that proposes a bootstrap function: https://www.r-bloggers.com/finding-correlations-in-data-with-uncertainty/
> >
> > weighted: I do weighted correlations with the wCorr package.
> >
> > Now I want to combine both approaches in one approach for a final analysis. How would you do that?
> >
> > Thanks for the help!
> >
> > Frederik Feys
> > PhD Medical Sciences
> > Onafhankelijk Methodoloog
> > https://www.researchgate.net/profile/Frederik_Feys
> > +32488020010
> >
> >
> >
> >
> >
> >
> >
> >         [[alternative HTML version deleted]]
> >
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