Dear Uwe, You are wrong. First, I've read the help file before submitting the report. For two variables, use="pairwise.complete.obs" and use="complete.obs" should be equivalent, shouldn't it? Of sourse, the results will be different when we have more than 2 variables. Second, with the call you proposed I am also getting incorrect result:
> cor(x, y, use="pairwise.complete.obs", method="s") [1] -0.1428571 The correct result is -0.4, as correctly calculated by cor.test() Regards Marek Ancukiewicz > X-Original-To: [EMAIL PROTECTED] > Date: Fri, 09 Apr 2004 19:06:47 +0200 > From: Uwe Ligges <[EMAIL PROTECTED]> > Organization: Fachbereich Statistik, Universitaet Dortmund > X-Accept-Language: en-us, en, de-de, de > Cc: [EMAIL PROTECTED] > > [EMAIL PROTECTED] wrote: > > Full_Name: Marek Ancukiewicz > > Version: 1.8.1 > > OS: Linux > > Submission from: (NULL) (132.183.12.87) > > > > > > Function cor() incorrectly handles missing observation with method="spearman": > > > > > >>x <- c(1,2,3,NA,5,6) > >>y <- c(4,NA,2,5,1,3) > >>cor(x,y,use="complete.obs",method="s") > > > > [1] -0.1428571 > > > >>cor(x[!is.na(x)&!is.na(y)],y[!is.na(x)&!is.na(y)],method="s") > > > > [1] -0.4 > > > > These two results should be the same. > > > > > No! Please read at least the help file, ?cor, before submitting a bug > report: > > > "If use is "complete.obs" then missing values are handled by casewise > deletion. Finally, if use has the value "pairwise.complete.obs" then the > correlation between each pair of variables is computed using all > complete pairs of observations on those variables." > > > Hence > cor(x, y, use="pairwise.complete.obs", method="s") > is what you expect ... > > Uwe Ligges > ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-devel
