Here’s a very simple way to include p-levels in Sweave. Let’s assume you want to mention a correlation coefficient in your text, \Swexpr{} will do just that.

\Sexpr{round(cor.test(x, y)$estimate,2)}

You can easily include the p-level, too.

\Sexpr{round(cor.test(x, y)$p.value,2)}

Except that’s not how it’s usually done. Normally we report whether the p-value is smaller than a certain threshold, and by convention only a few of them are considered.

Enter a very simple function (I’d include this in my first Sweave block where I load the data):

plevel <- function (x, strict=FALSE) {
  # levels of p-values, for Sweave
  # strict cuts at 0.05, otherwise cuts at 0.1
  if (x>0.1 & strict==FALSE) p <- "p>0.1"  # not significant
  if (x>0.1 & strict==TRUE)  p <- "p>0.05" # not significant
  if (x<=0.1 & strict==FALSE) p <- "p<0.1"  # significant
  if (x<=0.1 & strict==TRUE)  p <- "p>0.05" # not significant
  if (x<=0.01)  p <- "p<0.01"  # significant
  if (x<=0.05)  p <- "p<0.05"  # significant
  if (x<=0.001) p <- "p<0.001" # significant
  return(p)
  }

Created by Pretty R at inside-R.org

This automatizes the procedure, and the cited thresholds will always be correct. I could make this function simpler by leaving out the strict argument, or obviously adjust the thresholds.

So, here’s how I use this in Sweave: some text ($r=\Sexpr{round(cor.test(x, y)$estimate,2)}$, $\Sexpr{plevel(cor.test(x, y)$p.value)}$) some more text.

The dollar signs (math mode) mean that I get nice typography for the numbers and operators.