There are two main functions that I use, format.pval
and this one that I ripped from gforge and tweaked.
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)
tmp <- data.frame(summary(lm.D9)$coef)
tmp <- setNames(tmp, colnames(summary(lm.D9)$coef))
tmp[ , 4] <- format.pval(tmp[ , 4], eps = .001, digits = 2)
tmp
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) 5.032 0.2202177 22.85012 <0.001
# groupTrt -0.371 0.3114349 -1.19126 0.25
I like this one because it removes precision from pvalues > .1 (or whatever threshold you like if you want something different; that is, regardless of digits
, it only keeps two decimal places if the values is > .1), keeps trailing zeros (see example below), and adds in the < like you want for some level of precision (here 0.001).
pvalr <- function(pvals, sig.limit = .001, digits = 3, html = FALSE) {
roundr <- function(x, digits = 1) {
res <- sprintf(paste0('%.', digits, 'f'), x)
zzz <- paste0('0.', paste(rep('0', digits), collapse = ''))
res[res == paste0('-', zzz)] <- zzz
res
}
sapply(pvals, function(x, sig.limit) {
if (x < sig.limit)
if (html)
return(sprintf('< %s', format(sig.limit))) else
return(sprintf('< %s', format(sig.limit)))
if (x > .1)
return(roundr(x, digits = 2)) else
return(roundr(x, digits = digits))
}, sig.limit = sig.limit)
}
And examples:
pvals <- c(.133213, .06023, .004233, .000000134234)
pvalr(pvals, digits = 3)
# [1] "0.13" "0.060" "0.004" "< 0.001"
?format.pval
format.pval(summary(lm.D9)$coef[ , 4], eps = .001, digits = 2)
– Dogwood