This is pretty kludgy but ...

res.p <- capture.output(res)   # creates a list of what goes to the screen
res.pl <- '' "   # initialize res.pl
res.nul <- sapply(res.p,function(x.c) res.pl <<- paste(res.pl,res.c,sep='\n'))  # adds the list items separated by a line feed
text(x, y, res.pl, pos=4, cex=mycex)

This will replicate the print object for the t.test that goes to the screen so you can add it to a plot. One note, the output of several lines will be left justified at the x-location but centered vertically on the y-location. Experimental with the cex setting to fit it on your plot. It will also put two blank lines above and one below so you might strip those out for better positioning

Best regards

David Stevens

On 9/16/2021 8:59 AM, Bert Gunter wrote:
I was wrong. text() will attempt to coerce to character. This may be
informative:

as.character(res)
[1] "c(W = 0.992709285275917)"    "0.869917232073854"
[3] "Shapiro-Wilk normality test" "rnorm(100)"

plot(0:1, 0:1); text(0,seq(.1,.9,.2), labels = res, pos = 4)

Bert

Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Thu, Sep 16, 2021 at 7:44 AM Bert Gunter <bgunter.4...@gmail.com> wrote:
res is a list of class "htest" . You can only add text strings  to a
plot via text(). I don't know what ggplot does.

Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Thu, Sep 16, 2021 at 7:22 AM PIKAL Petr <petr.pi...@precheza.cz> wrote:
Dear all

I know I have seen the answer somewhere but I am not able to find it. Please
help

plot(1,1)
res <- shapiro.test(rnorm(100))
res
         Shapiro-Wilk normality test

data:  rnorm(100)
W = 0.98861, p-value = 0.5544

I would like to add whole res object to the plot.

I can do it one by one
text(locator(1), res$method)
text(locator(1), as.character(res$p.value))
...
But it is quite inconvenient

I could find some way in ggplot world but not in plain plot world.

Best regards
Petr
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