om: David Chertudi
To: arun
Cc: R help
Sent: Monday, September 9, 2013 2:29 PM
Subject: Re: [R] Mann-Whitney by group
Hello Arun,
Thanks so much--while I haven't tried it yet, this seems as though it
will be an excellent way to skip the categories (Actb, etc) that have
missing values (N
")$p.value}))
> # Bcl2 Ccl5 Cd27 Cd28
> #0.1250 0.1875 0.8125 0.8125
>
> A.K.
>
>
>
> - Original Message -
> From: David Chertudi
> To: R. Michael Weylandt
> Cc: "r-help@r-project.org"
> Sent: Sunday, September 8, 2013 11:13 PM
0.8125 0.8125
A.K.
- Original Message -
From: David Chertudi
To: R. Michael Weylandt
Cc: "r-help@r-project.org"
Sent: Sunday, September 8, 2013 11:13 PM
Subject: Re: [R] Mann-Whitney by group
The time has come to shake the cobwebs off of this analysis. I have
more data
The time has come to shake the cobwebs off of this analysis. I have
more data now and need to run the same tests, the same way as above.
My question is this--some of the pairs include NAs, and so are gumming
up the works. I'm not sure how to exclude them using the lhs ~ rhs
syntax. Any ideas her
On 2012-07-17 05:13, R. Michael Weylandt wrote:
On Mon, Jul 16, 2012 at 3:39 PM, Oxenstierna wrote:
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 fa
On Mon, Jul 16, 2012 at 3:39 PM, Oxenstierna wrote:
> 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
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
Untested, I think you need to lapply() over thing with some sort of extractor:
lapply(thing, function(x) x[['p.value']])
Michael
On Jul 10, 2012, at 3:45 PM, Oxenstierna wrote:
> This works very well--thanks so much.
>
> By way of extension: how would one extract elements from the result obj
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
David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77843-4352
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of Oxenstierna
> Sent: Friday, July 0
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
Can you describe how your data is organized. It is clear there are eight
columns, but it is not clear how the groups are represented, a Group column
or do the groups have to be assembled from information in another column (a
column with CD8.14, etc)? Create a small version of the data and use dput(
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