At 5:02 PM +0000 11/29/10, Adaikalavan Ramasamy wrote:

>Thanks for providing the example but it would be useful to know who

>I am communicating with or from which institute, but nevermind ...

>

>I don't know much about this subject but a quick google search gives

>me the following site:

http://davidmlane.com/hyperstat/A50760.html>

>Using the info from that website, I can code up the following to

>give the two-tailed p-value of difference in correlations:

>

> diff.corr <- function( r1, n1, r2, n2 ){

>

> Z1 <- 0.5 * log( (1+r1)/(1-r1) )

> Z2 <- 0.5 * log( (1+r2)/(1-r2) )

>

> diff <- Z1 - Z2

> SEdiff <- sqrt( 1/(n1 - 3) + 1/(n2 - 3) )

> diff.Z <- diff/SEdiff

>

> p <- 2*pnorm( abs(diff.Z), lower=F)

> cat( "Two-tailed p-value", p , "\n" )

> }

>

> diff.corr( r1=0.5, n1=100, r2=0.40, n2=80 )

> ## Two-tailed p-value 0.4103526

>

> diff.corr( r1=0.1, n1=100, r2=-0.1, n2=80 )

> ## Two-tailed p-value 0.1885966

>

>The p-value here is slightly different from the Vassar website

>because the website rounds it's "diff.Z" values to 2 digits.

>

>Regards, Adai

>

See also r.test in the psych package which will test for the

difference between two independent correlations as well as the more

complicated case of two dependent correlations.

> r.test(n=100,r12=.5,r34=.4, n2=80)

Correlation tests

Call:r.test(n = 100, r12 = 0.5, r34 = 0.4, n2 = 80)

Test of difference between two independent correlations

z value 0.82 with probability 0.41

>

r.test(n=100, .1,-.1,n2=80)

> r.test(n=100, .1,-.1,n2=80)

Correlation tests

Call:r.test(n = 100, r12 = 0.1, r34 = -0.1, n2 = 80)

Test of difference between two independent correlations

z value 1.31 with probability 0.19

>

Bill

>

>On 29/11/2010 15:30, syrvn wrote:

>>

>>Hi,

>>

>>based on the sample size I want to calculate whether to correlation

>>coefficients are significantly different or not. I know that as a first step

>>both coefficients

>>have to be converted to z values using fisher's z transformation. I have

>>done this already but I dont know how to further proceed from there.

>>

>>unlike for correlation coefficients I know that the difference for z values

>>is mathematically defined but I do not know how to incorporate the sample

>>size.

>>

>>I found a couple of websites that provide that service but since I have huge

>>data sets I need to automate this procedure.

>>

>>(

http://faculty.vassar.edu/lowry/rdiff.html)

>>

>>Can anyone help?

>>

>>Cheers,

>>syrvn

>>

>

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>

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>

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https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide

http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.