Is Wilcoxon test appropiate for the comparison of large, independent, nonnormal datasets?

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Hi all!
I am using 'ranksum' function (Wilcoxon test) to compare two independent, nonnormal, large data sets. However, p-value is 0 I think because of the effect of large data size. Any other test statistics that may handle such a large population analysis?
Thanks in advance :)

Accepted Answer

Star Strider
Star Strider on 17 Aug 2024
Since we’re likely discussing the lognormally distributed data you previously described, and since this is an unpaired comparision, ranksum is appropriate. A p value of 0 is an excellent result if you want to demonstrate that any two results ar different, since that indicates that they are and that the calculated probability is below the ability of floating-point arithmetic to calculate any other value ().
You can also use friedman to do multiple comparisons.
  2 Comments
Sara Woods
Sara Woods on 17 Aug 2024
Thanks again @Star Strider, maybe I should learn about multiple comparisons (e.g., Friedman test) and corrections (e.g., Bonferroni). I am using 'ranksum' because it's simpler to code! But maybe it's appropiate to strengthen my statistical analysis
Star Strider
Star Strider on 17 Aug 2024
As always, my pleasure!
Using ranksum is correct for a comparison of two vectors. I would use multcompare specifying 'friedman' in the ‘stats’ structure to do multiple comparisons. For 'CriticalValueType', I was always taught to use 'scheffe', however that may reflect the comparisons I was doing.

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