There is R code for both the Fisher transform and the corresponding bootstrap procedure in the vignette for the proto package: http://cran.r-project.org/doc/vignettes/proto/proto.pdf
On 7/26/07, Viechtbauer Wolfgang (STAT) <[EMAIL PROTECTED]> wrote: > Let r_1 be the correlation between the two variables for the first group with > n_1 subjects and let r_2 be the correlation for the second group with n_2 > subjects. Then a simple way to test H0: rho_1 = rho_2 is to convert r_1 and > r_2 via Fisher's variance stabilizing transformation ( z = 1/2 * ln[ > (1+r)/(1-r)] ) and then calculate: > > (z_1 - z_2) / sqrt( 1/(n_1 - 3) + 1/(n_2 - 3) ) > > which is (approximately) N(0,1) under H0. So, using alpha = .05, you can > reject H0 if the absolute value of the test statistic above is larger than > 1.96. > > -- > Wolfgang Viechtbauer > Department of Methodology and Statistics > University of Maastricht, The Netherlands > http://www.wvbauer.com/ > > > > ----Original Message---- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Timo Stolz Sent: > Thursday, July 26, 2007 16:13 To: [email protected] > Subject: [R] significance test for difference of two correlations > > > Dear R users, > > > > how can I test, whether two correlations differ significantly. (I > > want to prove, that variables are correlated differently, depending > > on the group a person is in.) > > > > Greetings from Freiburg im Breisgau (Germany), > > Timo Stolz > > ______________________________________________ > [email protected] 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. > ______________________________________________ [email protected] 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.
