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

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Sara Woods 2024-8-17，17:14

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评论： Star Strider 2024-8-17，18:43

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 :)

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Answer 1

Star Strider 2024-8-17，17:24

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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.

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Sara Woods 2024-8-17，17:32

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 2024-8-17，18:43

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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