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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