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

[Abby Spurdle]

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
>
>
>
>
>
>
>
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