Thank you, but this now sounds more difficult: what would be the point in having these ready-made functions if I have to do it manually? Anyway, How would I implement the last part?
On Thu, Mar 23, 2023 at 1:23 AM Ebert,Timothy Aaron <teb...@ufl.edu> wrote: > > If you are open to other options: > The null hypothesis is that there is no difference. > If I have two equations y=x and y=z and there is no difference then it > would not matter if an observation was from x or z. > Randomize the x and z observations. For each randomization calculate a > correlation for y=x and for y=z. > At each iteration calculate the absolute value of the difference in the > correlations. > Generate a frequency distribution from 100,000+ randomizations. > Find the observed difference in the frequency from random distributions. > What proportion of observations are as large or larger than the observed. > This is your p-value. > > Tim > > -----Original Message----- > From: R-help <r-help-boun...@r-project.org> On Behalf Of Luigi Marongiu > Sent: Wednesday, March 22, 2023 5:12 PM > To: r-help <r-help@r-project.org> > Subject: [R] How to test the difference between paired correlations? > > [External Email] > > Hello, > I have three numerical variables and I would like to test if their > correlation is significantly different. > I have seen that there is a package that "Test the difference between two > (paired or unpaired) correlations". > [https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.personality-project.org%2Fr%2Fhtml%2Fpaired.r.html&data=05%7C01%7Ctebert%40ufl.edu%7C35f2e7d6d9e844553c6408db2b1a337f%7C0d4da0f84a314d76ace60a62331e1b84%7C0%7C0%7C638151163767327230%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=S5T%2F1r%2BotV2BeL7S8bQFR0Avi4jDOuRX8N7LxACA6jg%3D&reserved=0] > However, there is the need to convert the correlations to "z scores using the > Fisher r-z transform". I have seen that there is another package that does > that > [https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsearch.r-project.org%2FCRAN%2Frefmans%2FDescTools%2Fhtml%2FFisherZ.html&data=05%7C01%7Ctebert%40ufl.edu%7C35f2e7d6d9e844553c6408db2b1a337f%7C0d4da0f84a314d76ace60a62331e1b84%7C0%7C0%7C638151163767327230%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=gI3vIHV5UnFbPSmeMyuCVvg9hpFCdF33qNgAXmOQOXU%3D&reserved=0]. > Yet, I do not understand how to process the data. Shall I pass the raw data > or the correlations directly? > > I have made the following working example: > ``` > # define data > v1 <- c(62.480, 59.492, 74.060, 88.519, 91.417, 53.907, 64.202, 62.426, > 54.406, 88.117) > v2 <- c(56.814, 42.005, 56.074, 65.990, 81.572, 53.855, 50.335, 63.537, > 41.713, > 78.265) > v3 <- c(54.170, 64.224, 57.569, 85.089, 104.056, 48.713, 61.239, 60.290, > 67.308, 71.179) > # visual exploration > par(mfrow=c(2, 1)) > plot(v2~v1, ylim=c(min(c(v1,v2,v3)), max(c(v1,v2,v3))), > xlim=c(min(c(v1,v2,v3)), max(c(v1,v2,v3))), > main="V1 vs V2") > abline(lm(v2~v1)) > plot(v3~v1, ylim=c(min(c(v1,v2,v3)), max(c(v1,v2,v3))), > xlim=c(min(c(v1,v2,v3)), max(c(v1,v2,v3))), > main="V1 vs V3") > abline(lm(v3~v1)) > ## test differences in correlation > # convert raw data into z-scores > library(psych) > library(DescTools) > FisherZ(v1) # I cannot convert the raw data into z scores (same for the other > variables): > > [1] NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Warning message: > > In log((1 + rho)/(1 - rho)) : NaNs produced > # convert correlations into z scores > # (the correlation score of 0.79 has been converted into 1.08; is this > correct?) > FisherZ(lm(v2~v1)$coefficients[2]) > > v1 > > 1.081667 > lm(v2~v1)$coefficients[2] > > v1 > > 0.7938164 > # apply test > v1_v2 = FisherZ(lm(v2~v1)$coefficients[2]) > v1_v3 = FisherZ(lm(v3~v1)$coefficients[2]) > paired.r(v1_v2, v1_v3, yz=NULL, length(v1), n2=NULL, twotailed=TRUE) > > Call: paired.r(xy = v1_v2, xz = v1_v3, yz = NULL, n = length(v1), n2 = NULL, > > twotailed = TRUE) > > [1] "test of difference between two independent correlations" > > z = NaN With probability = NaNWarning messages: > > 1: In log((1 + xy)/(1 - xy)) : NaNs produced > > 2: In log((1 + xz)/(1 - xz)) : NaNs produced > ``` > > What is the right way to run this test? > Shall I apply also yz? > Thank you > > -- > Best regards, > Luigi > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-help&data=05%7C01%7Ctebert%40ufl.edu%7C35f2e7d6d9e844553c6408db2b1a337f%7C0d4da0f84a314d76ace60a62331e1b84%7C0%7C0%7C638151163767327230%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=C%2FnA51iGPdivPDSPOktAvvb7r%2BjACQCqvcAc5jVMPew%3D&reserved=0 > PLEASE do read the posting guide > https://nam10.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.r-project.org%2Fposting-guide.html&data=05%7C01%7Ctebert%40ufl.edu%7C35f2e7d6d9e844553c6408db2b1a337f%7C0d4da0f84a314d76ace60a62331e1b84%7C0%7C0%7C638151163767327230%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=wKr4mBr%2ByPybzuj1xUzD1a75yfLHQ9uagaUfrE%2F6JDk%3D&reserved=0 > and provide commented, minimal, self-contained, reproducible code. -- Best regards, Luigi ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
