I plan to do a simulation study where I compare the performance of several robust correlation techniques with different distributions (skewed, with outliers, etc.). With

robust, I mean the ideal case of being robust against a) skewed distributions, b) outliers, and c) heavy tails.Along with the Pearson correlation as a baseline, I was thinking to include following more robust measures:

- Spearman’s ρ
- Percentage bend correlation (Wilcox, 1994, [1])
- Minimum volume ellipsoid, minimum covariance determinant (
`cov.mve`

/`cov.mcd`

with the`cor=TRUE`

option)- Probably, the winsorized correlation
Of course there are many more options (especially if you include robust regression techniques as well), but I want to restrict myself to the mostly used/ mostly promising approaches.

Now I have three questions (feel free to answer only single ones):

Are there other robust correlational methods I could/ should include?Which robust correlation techniques areactuallyused in your field?

_{(Speaking for psychological research: Except Spearman’s ρ\rho, I have never seen any robust correlation technique outside of a technical paper. Bootstrapping is getting more and more popular, but other robust statistics are more or less non-existent so far).}Are there already systematical comparisons of multiple correlation techniques that you know of?Also feel free to comment the list of methods given above.

[1] Wilcox, R. R. (1994). The percentage bend correlation coefficient.

Psychometrika, 59, 601-616.

**Answer**

Coming from a psychology perspective, Pearson and Spearman’s correlation do appear to be the most common. However, I think a lot of researchers in psychology engage in various data manipulation procedures on constituent variables prior to performing Pearson’s correlation. I imagine any examination of robustness should consider the effects of:

**transformations**of one or both variables in order to make variables approximate a normal distribution**adjustment or deletion of outliers**based on a statistical rule or knowledge of problems with an observation

**Attribution***Source : Link , Question Author : Community , Answer Author :
Jeromy Anglim
*