how to get higher precision p value output

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how to get higher precision p value output

anikaM
Hi,

I am running this function:

library(psych)
corr.test.col.1to3 <- corr.test(allF[1:3], method = "spearman", use =
"complete.obs")
names(corr.test.col.1to3)
corr.test.col.1to3$p

and my result looks like this:

> corr.test.col.1to3$p
           B_NoD    B_DwoC B_DwC
B_NoD  0.0000000 0.0000000     1
B_DwoC 0.0000000 0.0000000     1
B_DwC  0.6501836 0.6501836     0

Does anyone know how to get higher precision for those p values
instead of 0.0000000?

I tried:
corr.test.col.1to3 <- corr.test(allF[1:3], method = "spearman", use =
"complete.obs",minlength=20)

but it didn't change anything

if I do:
> str(corr.test.col.1to3)
List of 11
 $ r     : num [1:3, 1:3] 1 1 0.0139 1 1 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
  .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
 $ n     : num 1068
 $ t     : num [1:3, 1:3] Inf Inf 0.454 Inf Inf ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
  .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
 $ p     : num [1:3, 1:3] 0 0 0.65 0 0 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
  .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
 $ se    : num [1:3, 1:3] 0 0 0.0306 0 0 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
  .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
 $ sef   : num 0.0306
 $ adjust: chr "holm"
 $ sym   : logi TRUE
 $ ci    :'data.frame':    3 obs. of  4 variables:
  ..$ lower: num [1:3] NaN -0.0461 -0.0461
  ..$ r    : num [1:3] 1 0.0139 0.0139
  ..$ upper: num [1:3] NaN 0.0738 0.0738
  ..$ p    : num [1:3] 0 0.65 0.65
 $ ci.adj:'data.frame':    3 obs. of  2 variables:
  ..$ lower.adj: num [1:3] NaN -0.0461 -0.0547
  ..$ upper.adj: num [1:3] NaN 0.0738 0.0824
 $ Call  : language corr.test(x = allF[1:3], use = "complete.obs",
method = "spearman")
 - attr(*, "class")= chr [1:2] "psych" "corr.test"

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Re: how to get higher precision p value output

Eric Berger
> set.seed(1)
> m <- matrix(rnorm(500),ncol=2)
> cor(m)
#             [,1]       [,2]
#  [1,] 1.00000000 0.04060113
#  [2,] 0.04060113 1.00000000

> options(digits=12)
> cor(m)
#                 [,1]            [,2]
# [1,] 1.0000000000000 0.0406011304584
# [2,] 0.0406011304584 1.0000000000000

HTH,
Eric


On Tue, Nov 5, 2019 at 7:02 PM Ana Marija <[hidden email]>
wrote:

> Hi,
>
> I am running this function:
>
> library(psych)
> corr.test.col.1to3 <- corr.test(allF[1:3], method = "spearman", use =
> "complete.obs")
> names(corr.test.col.1to3)
> corr.test.col.1to3$p
>
> and my result looks like this:
>
> > corr.test.col.1to3$p
>            B_NoD    B_DwoC B_DwC
> B_NoD  0.0000000 0.0000000     1
> B_DwoC 0.0000000 0.0000000     1
> B_DwC  0.6501836 0.6501836     0
>
> Does anyone know how to get higher precision for those p values
> instead of 0.0000000?
>
> I tried:
> corr.test.col.1to3 <- corr.test(allF[1:3], method = "spearman", use =
> "complete.obs",minlength=20)
>
> but it didn't change anything
>
> if I do:
> > str(corr.test.col.1to3)
> List of 11
>  $ r     : num [1:3, 1:3] 1 1 0.0139 1 1 ...
>   ..- attr(*, "dimnames")=List of 2
>   .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
>   .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
>  $ n     : num 1068
>  $ t     : num [1:3, 1:3] Inf Inf 0.454 Inf Inf ...
>   ..- attr(*, "dimnames")=List of 2
>   .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
>   .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
>  $ p     : num [1:3, 1:3] 0 0 0.65 0 0 ...
>   ..- attr(*, "dimnames")=List of 2
>   .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
>   .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
>  $ se    : num [1:3, 1:3] 0 0 0.0306 0 0 ...
>   ..- attr(*, "dimnames")=List of 2
>   .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
>   .. ..$ : chr [1:3] "B_NoD" "B_DwoC" "B_DwC"
>  $ sef   : num 0.0306
>  $ adjust: chr "holm"
>  $ sym   : logi TRUE
>  $ ci    :'data.frame':    3 obs. of  4 variables:
>   ..$ lower: num [1:3] NaN -0.0461 -0.0461
>   ..$ r    : num [1:3] 1 0.0139 0.0139
>   ..$ upper: num [1:3] NaN 0.0738 0.0738
>   ..$ p    : num [1:3] 0 0.65 0.65
>  $ ci.adj:'data.frame':    3 obs. of  2 variables:
>   ..$ lower.adj: num [1:3] NaN -0.0461 -0.0547
>   ..$ upper.adj: num [1:3] NaN 0.0738 0.0824
>  $ Call  : language corr.test(x = allF[1:3], use = "complete.obs",
> method = "spearman")
>  - attr(*, "class")= chr [1:2] "psych" "corr.test"
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.