Or if David's answer seems like too much work you could use the `mvrnorm` function in the MASS package to generate 2 vectors with the given correlation and sample size and feed those vectors to the `cor.test` function.
Or Pearson's test can be computed in 1 line of R code without needing any special functions: pt( print( r*sqrt( (n-2)/(1-r^2) ) ), n-2, lower=FALSE ) Or a test based on simulation (parametric bootstrap) can be constructed in a single line as well (though may be more readable and give other useful info if spread over a few lines): mean( replicate(100000, cor( rnorm(n),rnorm(n) )) >= r ) Which of these are actually more/less work depends on your current brand of lazyness. On Sun, Feb 24, 2013 at 4:12 PM, David Winsemius <dwinsem...@comcast.net>wrote: > > On Feb 24, 2013, at 1:29 PM, Martin Batholdy wrote: > > > Dear Miguel, > > > > thanks! > > But I actually do not have two vectors but just a correlation > coefficient and want to get the p value. > > As far as I can see it, cor.test only works when having raw data pairs > or am I missing something? > > > > > > You are ignoring the fact that the code is readily accessible. It first > calculates the cor() results and then works with it using that vale and the > numbers of cases. It doesn't seem to me that it should be at all difficult > to modify the code to take cor() and N and return a statistic of your > choosing. > > -- > David. > > On Feb 24, 2013, at 22:24 , Miguel Manese <jjon...@gmail.com> wrote: > > > >> Hi Martin, > >> > >> See ?cor.test > >> > >> example(cor.test) > >> > >> Regards, > >> - Jon > >> > >> On Mon, Feb 25, 2013 at 5:06 AM, Martin Batholdy > >> <batho...@googlemail.com> wrote: > >>> Hi, > >>> > >>> is there a predefined function that computes the p- or t-value > >>> based on a correlation coefficient and its sample size? > >>> > >>> > >>> thanks! > >>> > >>> ______________________________________________ > >>> R-help@r-project.org mailing list > >>> https://stat.ethz.ch/mailman/listinfo/r-help > >>> PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > >>> and provide commented, minimal, self-contained, reproducible code. > > > > ______________________________________________ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > David Winsemius > Alameda, CA, USA > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Gregory (Greg) L. Snow Ph.D. 538...@gmail.com [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
