summary
displays significance code for p.values. Is there a R function that convert p.value to significance code? for example: 0.02 --> '*'
and 0.005 --> '**'
?
P−value=Pr[χ211≥20.66], as the P-value is the probability of getting your observed test statistic or worse in the null distribution. The formula above tells you that the P-value can be calculated by evaluating the CCDF of the χ211 random variable!
The stars are only intended to flag levels of significance for 3 of the most commonly used levels. If a p-value is less than 0.05, it is flagged with one star (*). If a p-value is less than 0.01, it is flagged with 2 stars (**). If a p-value is less than 0.001, it is flagged with three stars (***).
Use symnum
as shown below. ?symnum
for more info.
p.values <- c(9.5e-15, 0.02)
Signif <- symnum(p.values, corr = FALSE, na = FALSE, cutpoints = c(0,
0.001, 0.01, 0.05, 0.1, 1), symbols = c("***", "**", "*", ".", " "))
giving:
> str(Signif)
Class 'noquote' atomic [1:2] *** *
..- attr(*, "legend")= chr "0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1"
The above code is used in R itself in stats::printCoefmat
(see ?printCoefmat
) which is called from stats:::print.summary.lm
. Note that it produces an object of class "noquote"
and also provides a legend in the "legend"
attribute.
Tracking down the code used by summary
, you can find the following in stats:::printCoefmat
:
Signif <- symnum(pv, corr = FALSE, na = FALSE,
cutpoints = c(0, 0.001, 0.01, 0.05, 0.1, 1),
symbols = c("***", "**", "*", ".", " "))
You can create your own function to do it, such as
signif.num <- function(x) {
symnum(x, corr = FALSE, na = FALSE, legend = FALSE,
cutpoints = c(0, 0.001, 0.01, 0.05, 0.1, 1),
symbols = c("***", "**", "*", ".", " "))
}
signif.num(c(1e-8, 0.01, 0.05, 0.1, 0.2))
(Note the last value is just a space and not visible in the output)
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