# Compare Pearson and Spearman correlation [closed]

I am working on a systematic review and want to compare the correlation of different devices.

Both Pearson as Spearman correlations are reported in papers. Because they both represent a correlation, is it possible to put them all in one database and compare them? Or is this not possible.

## closed as unclear what you're asking by Tim♦, Nick Cox, gung♦, Greenparker, whuber♦Jul 8 '16 at 13:34

Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

• What do you mean by "putting them all in one database"? What do you want to compare? Is it theoretical differences or some kind of performance comparison? – Tim Jul 8 '16 at 12:12
• I'm not sure what you're asking exactly, but if you wanted to do a meta-analysis, eg, you wouldn't use Pearson and Spearman interchangeably. – gung Jul 8 '16 at 12:33
• It's always useful to point out that the assumptions underlying these metrics differ. Pearson captures linear association while Spearman is a measure of monotonic (ordinal) association. Many other measures of nonlinear, pairwise association are out there including the MIC (mutual information criterion), distance correlations, Brownian correlation, reproducing kernel Hilbert spaces, etc. – DJohnson Jul 8 '16 at 12:40

## 1 Answer

I suggest you read this thread, which sheds an interesting light on differences between both coefficients in rather simple datasets. I guess, that afterwards you will probably decide not to mix them:

What is the explanation for having a Pearson's correlation coefficient significantly larger than the Spearman's rank correlation coefficient?

Edit: Greenparker is right in his comment, that I should explain here. In the thread I linked, I give an example of a dataset in which Pearson and Spearman differ a lot, as much as one being positive an the other being negative. A shorter example for the purpose of this thread would be the following in R:

> x=c(1.0, 1.01, 1.02, 1.03, 1.04,  100)
> y=c(0.04, 0.03, 0.02, 0.01, 0, 100)
> cor(x,y, method="spearman")
[1] -0.1428571
> cor(x,y, method="pearson")
[1] 0.9999998


As you can see, for the same six simple data points, Spearman is almost zero and negative whilst Pearson is almost 1. I think this should be illustrative enough, not to mix them as "almost the same".

We're looking for long answers that provide some explanation and context. Don't just give a one-line answer; explain why your answer is right, ideally with citations. Answers that don't include explanations may be removed.

• If you are only going to point to this thread, this should be a comment, not an answer. – gung Jul 8 '16 at 12:35
• While this link may answer the question, it is better to include the essential parts of the answer here and provide the link for reference. Link-only answers can become invalid if the linked page changes. - From Review – Greenparker Jul 8 '16 at 13:15
• @Greenparker You are right. I edited and added a short example that has the same essence as the much longer answer I gave in the other thread. I hope, that for the purpose of this thread, the shorter example is sufficient. – Bernhard Jul 8 '16 at 13:33