lapply(thing, function(x) x[['p.value']]) --works very well, thank you.
Not to be a chore, but I'm interested in comparing the results of
wilcox.test--and the methodology we've employed so far--with the results and
methodology of wilcox_test (library("coin")). So, I'd like to compare
groups 5 and
This works very well--thanks so much.
By way of extension: how would one extract elements from the result object?
For example:
thing<=apply(Dtb[,3:10], 2, function(x) wilcox.test(x~Dtb$Group))
summary(thing)$p.value
Does not provide a list of p-values as it would in a regression object.
Idea
Hi David,
Thank you for the insight: I could have sworn I added a picture of the
data, but providing the actual data is worlds easier to deal with, I'm sure.
I've never used dput(), so I entered it using the dataframe in question as
the object, and I've pasted the results below.
Essentially, I
I'm a fan of Ggobi--which works well with or without R--but I'm not sure how
it handles enormous data sets. I second the Tufte recommendation, and add:
Interactive and Dynamic Graphics for Data Analysis.
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