[R] how to get higher precision p value output

[Ana Marija]

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"