Hello all, I believe this can be done using bootstrap, but I am wondering if there is some other way that might be used to tackle this.
#Let's say I have two pairs of samples: set.seed(100) s1 <- rnorm(100) s2 <- s1 + rnorm(100) x1 <- s1[1:99] y1 <- s2[1:99] x2 <- x1 y2 <- s2[2:100] #And both yield the following two correlations: cor(x1,y1) # 0.7568969 (cor1) cor(x2,y2) # -0.2055501 (cor2) Now for my questions: 1) is cor1 larger then cor2? (CI for the diff ?) 2) With what P value? 3) What if the values of s1 are not independent ? I found an older thread discussing such issues: http://tolstoy.newcastle.edu.au/R/e2/help/06/09/1035.html But wasn't sure how much this might be relevant to my case. Thanks for any help, Tal ----------------Contact Details:------------------------------------------------------- Contact me: tal.gal...@gmail.com | 972-52-7275845 Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | www.r-statistics.com (English) ---------------------------------------------------------------------------------------------- [[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.
